Publications-Theses
Article View/Open
Publication Export
-
Google ScholarTM
NCCU Library
Citation Infomation
Related Publications in TAIR
題名 巨量資料生態：以模因學分析網路文本的進化
The Ecology of Big Data: A Memetic Approach on the Evolution of Online Text作者 柯政豪
Ke, Cheng Hao貢獻者 蕭乃沂
Hsiao, Naiyi
柯政豪
Ke, Cheng Hao關鍵詞 文字探勘
巨量資料
模因學
進化論
生態學
Text Mining
Big Data
Memetics
Darwinian Evolution
Ecology日期 2016 上傳時間 11-Jul-2016 17:43:20 (UTC+8) 摘要 公共行政學正面臨理論與方法無法結合的挑戰，這個問題在巨量資料的時代更是明顯，因為與人脫離的網路文本資料無法透過傳統的理論架構來解釋與分析，如果不引進新的本體論與認識論，公共行政學將遭遇無法深入分析巨量文本資料的困境。近代達爾文進化論因為透過複製者角度解釋自然界現象，所以能夠脫離以個別生物為核心的觀點，解釋過去無法分析的行為與動機。以進化論為基礎的模因學將社會文化的變化視為一種進化的過程，認為社會文化界的變化可以透過模因這種複製單位的進化來解釋，模因的觀點因為脫離以人為核心的角度，所以能夠解釋無法和使用者結合的網路文本資料。 本研究首先透過整合過去社會文化進化和模因學的研究，建構脫離使用者的巨量文本資料分析架構與假設，同時引入進化論與生態學中的方法與理論，驗證巨量網路文本背後的進化動態與機制。接著本研究針對Yahoo!奇摩新聞中探討「課綱微調」議題的1,761篇主文進行分析，透過中文斷詞與文本集群分析方法萃取出由不同模因類種建構的主文集群，並透過量化統計方法驗證個別集群文本特質與在時間上分布的趨勢對於整體主文集群變化的影響。結果發現個別模因類種本身在時間上的分布擁有密度依賴的關係，同時主文本身的情緒、字數等等特質，對產生的回文數也都有影響，但這些影響在不同密度的環境下會有所變化，網站版面環境本身也會與主文回文數有顯著的關係，而個別模因類種之間互動也都有顯著的正向交叉關係，另外模因類種也與詞彙組之間有顯著的正向和負向關係。 本研究的結果顯示以模因學探討巨量文本資料能夠允許研究者結合理論與文本探勘技術，以理論為出發點建構出能夠被驗證的假設，並引入進化論和生態學中的方法與架構進行資料的分析。研究發現由不同詞彙建構的文本數量在時間上的分布是一件必須觀察的現象，因為由類同詞彙建構的文本在過去時間點的變化，對於當下時間點類同主文的數量會有影響。同時文本特質和所處的網路環境也都是觀測網路文本變化時不可忽略的變數，因為這些因素對主文和回文的數量都有很重要的影響。另外分析網路文本時，應該以網站來區隔分析資料，因為網路環境同樣對於文本與回文的數量有影響。最後，出現在同一篇主文中機率高的詞彙組合也是會影響文本變化的重要因素之一。 本研究建議未來巨量文本資料的研究應該繼續以模因學的觀點出發，同時搭配具有不同優缺點的文本探勘技術與密度依賴檢定反覆驗證結果。未來的研究也宜朝向分析時間序列更長和出自不同網站的文本集，並建構能夠整合不同文本特質和環境影響的分析架構，另外納入文字以外的多媒體資料和以模因學角度設計的問卷調查資料進行探討。
The mismatch between theory and method is a crisis which the discipline of public administration cannot afford to ignore. The arrival of the “Era of Big Data”, only serves to make matters worse. As data becomes uncoupled with the individual, so goes any pretense of trying to provide analyses beyond that of mere description. If public administration refuses to import new ontology and epistemology, then very little could be gained from online text research. The Darwinian theory of evolution, ever since the Modern Synthesis, has embraced the replicator centered point of view when explaining all living phenomena. This has unshackled the theory from limitations of the traditional individual centered view of evolution. Memetics is a recent offshoot of the theory of evolution. It views social cultural change as a process based on the evolution of a cultural unit of selection, the meme. Due to memetics’ ability to explain social cultural evolution from the meme’s point of view, it is a natural candidate to examine the dynamics of “big” online text data. The first part of this research is on the construction of an online text analysis framework, with testable hypotheses, through the integration of past literature on evolution, social cultural evolution, memetics and ecology. The second part is concerned with the testing of the framework with empirical data. The text corpus used in this research contains 1,761 news reports from the Yahoo! News website on the issue of high school curriculum change. Chinese term segmentation and text clustering algorithms were applied to the corpus, in order to extract text quasi-species composed of similar memes. Statistical tests were then used to determine the influence of text characteristics and temporal distribution dynamics on the population of quasi-species. Findings indicate that the population dynamics of text quasi-species were influenced by density dependence. Text characteristics, such as word length and sentiment, also exert significant influence on the number of comments that each text receives. However, these influences are not equal under different density conditions. The location of the news articles within the website also creates a difference in the number of comments received. Finally, interactions between the temporal distribution of different quasi-species and between quasi-species and term groups also yielded significant positive and negative correlations. The results are proof that memetics is an ideal theoretical platform to connect theory with text mining/analysis methods. It allows for a theory based approach and the creation of testable hypotheses. Frameworks and methods based on evolution and ecological research are also applicable under memetics. The empirical findings point to the importance of monitoring the temporal distribution of online text, and the significance of text characteristics and website environments to text population changes. The results also illustrate the importance of term groups in the influence of text population dynamics. Together these variables and effects are all central to the understanding of the change in online text and comment numbers, and the effect of past text population on current population changes. Online texts from different websites should also be analyzed separately. This research recommends that future public administration big data analyses should continue to adopt the memetic approach. Nevertheless, attention should be given to the strengths and weaknesses of different text mining algorithms and density dependence tests. Big data time series from different websites and with longer temporal spans should also be considered, while social cultural artifacts other than texts should not be excluded from memetics based researches. New frameworks must also be constructed to integrate and understand, the interaction between important variables, such as, text characteristics and environmental influences. Findings on all forms of online data would also be enhanced through comparisons with results from questionnaires designed with memetics in mind.參考文獻 李仲彬（2013a）。政府創新的類型與分佈：我國地方政府1999-2010年間的觀察。公共行政學報，44，73-112。李仲彬（2013b）。影響地方政府創新產出量的因素。東吳政治學報，31(1)，105-160。林千翔、張嘉惠、陳貞伶（2010）。結合長詞優先與序列標記之中文斷詞研究。中文計算語言學期刊(International Journal of Computational Linguistics and Chinese Language Processing)，15(3-4)，161-180。高婉瑜（2014）。網路語言的語音模因及其傳播—以宅女小紅的作品為例。淡江中文學報，30，277-315。陳良駒、張正宏、陳日鑫（2010）。以特徵詞共現特性探討知識管理研究議題相關性—使用共詞與關聯法則分析。資訊管理研究，17(4)，31-60。陳稼興、謝佳倫、許芳誠（2000）。以遺傳演算法為基礎的中文斷詞研究。資訊管理研究，2(2)，27-44。廖洲棚、陳敦源、蕭乃沂、廖興中（2014）。運用巨量資料實踐良善治理：網路民意導入政府決策分析之可行性研究。行政院研究發展考核委員會（編號：RDEC-MIS-102-003），未出版。蕭乃沂、陳敦源、廖洲棚（2015）。政府應用巨量資料精進公共服務與政策分析之可行性研究。國家發展委員會（編號：NDC-MIS-103-003），未出版。蕭乃沂、黃東益（2015）。104年度網路輿情蒐集、分析及運用計畫結案報告。教育部青年發展署，未出版。Adar, E., & Adamic, L. A. (2005, 19-22 Sept. 2005). Tracking information epidemics in blogspace. Paper presented at the 2005 IEEE/WIC/ACM International Conference on Web Intelligence, 2005. Proceedings.Adar, E., Teevan, J., & Dumais, S. T. (2009). Resonance on the web: web dynamics and revisitation patterns. Paper presented at the Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, Boston, MA, USA. Adar, E., Zhang, L., Adamic, L., & Lukose, R. (2004). Implicit structure and the dynamics of blogspace. Paper presented at the Workshop on the Weblogging Ecosystem, 13th International World Wide Web Conference Aggarwal, C. C., & Zhai, C. (2012). A Survey of Text Clustering Algorithms. In C. C. Aggarwal & C. Zhai (Eds.), Mining Text Data (pp. 77-128): Springer US.Akcora, C. G., Bayir, M. A., Demirbas, M., & Ferhatosmanoglu, H. (2010). Identifying breakpoints in public opinion. Paper presented at the Proceedings of the First Workshop on Social Media Analytics, Washington D.C., District of Columbia. Alford, J. R., & Hibbing, J. R. (2004). The Origin of Politics: An Evolutionary Theory of Political Behavior. Perspectives on Politics, 2(04), 707-723. doi:doi:10.1017/S1537592704040460Álvarez, A. (2005). Three Memetic Theories of Technology. Techné, 9(2). Amiri, B., Fathian, M., & Maroosi, A. (2009). Application of shuffled frog-leaping algorithm on clustering. The International Journal of Advanced Manufacturing Technology, 45(1-2), 199-209. doi:10.1007/s00170-009-1958-2Ansolabehere, S., & Hersh, E. (2012). Validation: What Big Data Reveal About Survey Misreporting and the Real Electorate. Political Analysis, 20(4), 437-459. doi:10.1093/pan/mps023Arpin, S. L., & Cushing, J. (2008). Modeling frequency-dependent selection with an application to cichlid fish. Math Biosci Eng, 5, 889-903. Astill, S. (2004). Equipping ourselves to explore the political Galapagos: ideas, networks and evolution. Paper presented at the York University Department of Politics at the Political Science Workshop. Aunger, R. (2000). Darwinizing Culture: The Status of Memetics as a Science. United States: Oxford University Press.Aunger, R. (2002). The Electric Meme: A New Theory of How We Think: Free Press.Aunger, R. (2006). What`s the matter with memes? In A. Grafen & M. Ridley (Eds.), Richard Dawkins: How a Scientist Changed the Way We Think. United Kingdom: Oxford University Press.Bail, C. A. (2014). The cultural environment: measuring culture with big data. Theory and Society, 43(3-4), 465-482. doi:10.1007/s11186-014-9216-5Baker, M. C., & Gammon, D. E. (2008). Vocal memes in natural populations of chickadees: why do some memes persist and others go extinct? Animal Behaviour, 75(1), 279-289. doi:http://dx.doi.org/10.1016/j.anbehav.2007.05.022Ball, P. (2004). Critical Mass: How one thing leads to another. United States of America: Farrar, Straus and Giroux.Bangerter, A., & Heath, C. (2004). The Mozart effect: Tracking the evolution of a scientific legend. British Journal of Social Psychology, 43(4), 605-623. doi:10.1348/0144666042565353Barbrook, A. C., Howe, C. J., Blake, N., & Robinson, P. (1998). The phylogeny of The Canterbury Tales. Nature, 394(6696), 839-839. Retrieved from http://dx.doi.org/10.1038/29667Bauckhage, C. (2011). Insights into Internet Memes. Paper presented at the Proceedings of the Fifth International AAAI Conference on Weblogs and Social Media.Beil, F., Ester, M., & Xu, X. (2002). Frequent term-based text clustering. Paper presented at the Proceedings of the eighth ACM SIGKDD international conference on Knowledge discovery and data mining, Edmonton, Alberta, Canada. Bentley, R. A. (2010). Fashion versus Reason in the Creative Industries. In M. J. O`Brien & S. J. Shennan (Eds.), Innovation in Cultural Systems: Contributions from evolutionary anthropology. United States of America: Massachusetts Institute of Technology Press.Benzon, W. (1996). Culture as an evolutionary arena. Journal of Social and Evolutionary Systems, 19(4), 321-362. doi:http://dx.doi.org/10.1016/S1061-7361(96)90003-XBest, M. L. (1997). Models for Interacting Populations of Memes: Competition and Niche Behavior. Journal of Memetics - Evolutionary Models of Information Transmission, 1(2). Best, M. L. (1997b). An ecology of text: using text retrieval to study alife on the net. Artificial Life, 3(4), 261-287. Bettencourt, L. M. A., Cintrón-Arias, A., Kaiser, D. I., & Castillo-Chávez, C. (2006). The power of a good idea: Quantitative modeling of the spread of ideas from epidemiological models. Physica A: Statistical Mechanics and its Applications, 364, 513-536. doi:http://dx.doi.org/10.1016/j.physa.2005.08.083Bikhchandani, S., Hirshleifer, D., & Welch, I. (1992). A Theory of Fads, Fashion, Custom, and Cultural Change as Informational Cascades. Journal of Political Economy, 100(5), 992-1026. Retrieved from http://www.jstor.org/stable/2138632Bjørnstad, O. N., Ims, R. A., & Lambin, X. (1999). Spatial population dynamics: analyzing patterns and processes of population synchrony. Trends in Ecology & Evolution, 14(11), 427-432. Bjarneskans, H., Grønnevik, B., & Sandberg, A. (1997). The Lifecycle of Memes. http://www.aleph.se/Trans/Cultural/Memetics/memecycle.html Retrieved from http://www.aleph.se/Trans/Cultural/Memetics/memecycle.htmlBlackmore, S. (1999). The Meme Machine. United States: Oxford University Press Inc.Blackmore, S. (2000). The memes` eye view. In R. Aunger (Ed.), Darwinizing Culture: The Status of Memetics as a Science. United States: Oxford University Press.Blackmore, S. (2001). Evolution and Memes: The Human Brain as a Selective Imitation Device. Cybernetics and Systems: An International Journal, 32, 225-255. Blackmore, S. (2003). Consciousness in Meme Machines. Journal of Consciousness Studies, 10(4-5), 19-30. Retrieved from http://www.ingentaconnect.com/content/imp/jcs/2003/00000010/F0020004/1344Bleay, C., Comendant, T., & Sinervo, B. (2007). An experimental test of frequency-dependent selection on male mating strategy in the field. Proceedings of the Royal Society of London B: Biological Sciences, 274(1621), 2019-2025. Blute, M. (1979). Sociocultural evolutionism: An untried theory. Behavioral Science, 24(1), 46-59. doi:10.1002/bs.3830240107Blute, M. (2005). Memetics and evolutionary social science. Journal of Memetics - Evolutionary Models of Information Transmission, 9(1). Blute, M. (2010). Darwinian Sociocultural Evolution: Solutions to dilemmas in cultural and social theory. United States of America: Cambridge University Press.Borenstein, E. (2004). Survival of the Catchiest: Memes and Postmodern Russia. The Slavic and East European Journal, 48(3), 462-483. doi:10.2307/3220071Boushey, G. (2010). Policy Diffusion Dynamics in America. United States: Cambridge University Press.Boyd, D., & Crawford, K. (2012). Critical Questions for Big Data. Information, Communication & Society, 15(5), 662-679. doi:10.1080/1369118X.2012.678878Boyne, G. A. (1996). The Intellectual Crisis in British Public Administration: Is Public Management the Problem or the Solution? Public Administration, 74(4), 679-694. doi:10.1111/j.1467-9299.1996.tb00890.xBrook, B. W., & Bradshaw, C. J. A. (2006). Strength of Evidence for Density Dependence in Abundance Time Series of 1198 Species. Ecology, 87(6), 1445-1451. Retrieved from http://www.jstor.org/stable/20069094Bull, L., Holland, O., & Blackmore, S. (2000). On meme-gene coevolution. Artificial Life, 6(3), 227-235. doi:10.1162/106454600568852Bulmer, M. G. (1975). The Statistical Analysis of Density Dependence. Biometrics, 31(4), 901-911. doi:10.2307/2529815Burgess, J. (2008). All Your Chocolate Rain Are Belong to Us?` Viral Video, YouTube and the Dynamics of Participatory Culture. In G. Lovink & R. S. Miles (Eds.), The VideoVortex Reader: Responses to YouTube. Amsterdam: Institute of Network Cultures.Burt, R. S. (1987). Social contagion and innovation: Cohesion versus structural equivalence. American Journal of Sociology, 1287-1335. Buss, D. M., Shackelford, T. K., Kirkpatrick, L. A., & Larsen, R. J. (2001). A Half Century of Mate Preferences: The Cultural Evolution of Values. Journal of Marriage and Family, 63(2), 491-503. doi:10.2307/3654608Butts, C. T., & Hilgeman, C. (2003). Inferring Potential Memetic Structure from Cross-Sectional Data: An Application to American Religious Beliefs. Journal of Memetics - Evolutionary Models of Information Transmission, 1(7). Calsbeek, R., Bonvini, L., & Cox, R. M. (2010). Geographic Variation, Frequency-Dependent Selection, and the Maintenance of a Female-Limited Polymorphism. Evolution, 64(1), 116-125. Retrieved from http://www.jstor.org/stable/27743496Cambria, E., Schuller, B. r., Yunqing, X., & Havasi, C. (2013). New Avenues in Opinion Mining and Sentiment Analysis. Intelligent Systems, IEEE, 28(2), 15-21. doi:10.1109/MIS.2013.30Campbell, D. T. (1960). Blind Variation and Selective Retention in Creative Thought as in Other Knowledge Processes. Psychological Review, 67(6), 380-400. Campbell, D. T. (1979). Comments on the sociobiology of ethics and moralizing. Behavioral Science, 24(1), 37-45. Campbell, D. T. (1982). Evolutionary epistemology. In H. C. Plotkin (Ed.), Learning, Development, and Culture: Essays in evolutionary epistemology. United States of America: John Wiley & Sons Ltd.Castelfranchi, C. (2001). Towards a Cognitive Memetics: Socio-Cognitive Mechanisms for Memes Selection and Spreading. Journal of Memetics - Evolutionary Models of Information Transmission, 5(1). Cavalli-Sforza, L. L., & Feldman, M. W. (1981). Cultural Transmission and Evolution: A Quantitative Approach. United Kingdom: Princeton University Press.Cenettlsr, H., & McGill, P. (1996). Random genetic drift in the female germline explains the rapid segregation of mammalian mitochondrial DNA. Nature genetics, 14. Centers for Disease Control and Prevention. (2012). Principles of Epidemiology in Public Health Practice Chang, P.-C., Galley, M., & Manning, C. D. (2008). Optimizing Chinese word segmentation for machine translation performance. Paper presented at the Proceedings of the Third Workshop on Statistical Machine Translation, Columbus, Ohio. Chatfield, C. (1996). The Analysis of Time Series: An Introduction (5th ed.). Great Britain: Chapman & Hall.Chen, C. L. P., & Zhang, C.-Y. (2014). Data-intensive applications, challenges, techniques and technologies: A survey on Big Data. Information Sciences, In Press, Corrected Proof. Chen, M., Mao, S., & Liu, Y. (2014). Big Data: A Survey. Mobile Networks and Applications, 19(2), 171-209. doi:10.1007/s11036-013-0489-0Chiang, T.-H., Chang, J.-S., Lin, M.-Y., & Su, K.-Y. (1992). Statistical Models for Word Segmentation and Unknown Word Resolution. Paper presented at the 5th R.O.C. Computational Linguistics Conference. Chick, G. (2001). Culture-Bearing Units and the Units of Culture: An Introduction. Cross-Cultural Research, 35(2), 91-108. Chielens, K., & Heylighen, F. (2005). Operationalization of Meme Selection Criteria: Methodologies to Empirically Test Memetic Predictions. Paper presented at the Joint Symposium on Socially Inspired Computing Chielens, K., & Heylighen, F. (2005). Operationalization of meme selection criteria: Methodologies to empirically test memetic predictions. Proceedings of the Joint Symposium on Socially Inspired Computing (AISB’05), 14–20. doi:citeulike-article-id:8877404Coker, C. (2008). War, Memes and Memeplexes. International Affairs (Royal Institute of International Affairs 1944-), 84(5), 903-914. doi:10.2307/25144927Colbaugh, R., & Glass, K. (2012). Early warning analysis for social diffusion events. Security Informatics, 1(18). doi:10.1109/ISI.2010.5484778Collins, A., Hart, E. M., & Molofsky, J. (2010). Differential response to frequency-dependent interactions: an experimental test using genotypes of an invasive grass. Oecologia, 164(4), 959-969. doi:10.1007/s00442-010-1719-9Connell, J. H., & Green, P. T. (2000). Seedling Dynamics over Thirty-Two Years in a Tropical Rain Forest Tree. Ecology, 81(2), 568-584. doi:10.2307/177449Conte, R. (2000). Memes through (social) minds. In R. Aunger (Ed.), Darwinizing Culture: The Status of Memetics as a Science. United States: Oxford University Press.Corley, C. D., Cook, D. J., Mikler, A. R., & Singh, K. P. (2010). Text and structural data mining of influenza mentions in web and social media. International journal of environmental research and public health, 7(2), 596-615. Cowpertwait, P. S. P., & Metcalfe, A. V. (2009). Introductory Time Series with R. United States of America: Springer Science+Business Media.Crawford, K., Miltner, K., & Gray, M. L. (2014). Critiquing Big Data: Politics, Ethics, Epistemology. International Journal of Communication, 8, 1663-1672. Cryer, J. D., & Chan, K.-S. (2008). Time Series Analysis: With Applications in R (2nd ed.). United States of America: Springer Science+Business Media, LLC.Csikszentmihalyi, M. (1993). The Evolving Self: A psychology for the third millennium. United States of America: HarperCollins Publishers, Inc.Cumbley, R., & Church, P. (2013). Is “Big Data” creepy? Computer Law & Security Review, 29(5), 601-609. doi:http://dx.doi.org/10.1016/j.clsr.2013.07.007Dale, M. R. T., & Fortin, M.-J. (2002). Spatial autocorrelation and statistical tests in ecology. Écoscience, 9(2), 162-167. Retrieved from http://www.jstor.org/stable/42901480Daley, D. J., & Kendall, D. G. (1965). Stochastic Rumours. IMA Journal of Applied Mathematics, 1(1), 42-55. doi:10.1093/imamat/1.1.42Damanpour, F. (1991). Organizational Innovation: A Meta-Analysis of Effects of Determinants and Moderators. The Academy of Management Journal, 34(3), 555-590. doi:10.2307/256406Davis, C. B. (2007). Cultural Evolution and Performance Genres: Memetics in Theatre History and Performance Studies. Theatre Journal, 59(4), 595-614. Dawkins, R. (1976). The Selfish Gene (30th anniversary ed.). United States: Oxford University Press Inc.Dawkins, R. (1982). The Extended Phenotype: The long reach of the gene. United States of America: Oxford University Press.de Jong, M. (1999). Survival of the institutionally fittest concepts. Journal of Memetics - Evolutionary Models of Information Transmission, 3(1). De Tiége, A., Tanghe, K., Braeckman, J., & Van de Peer, Y. (2014). From DNA- to NA-centrism and the conditions for gene-centrism revisited. Biol Philos, 29(55-69). doi:10.1007/s10539-013-9393-zDennett, D. C. (1991). Consciousness Explained. United States of America: Little, Brown & Company.Dennett, D. C. (1995). Darwin`s Dangerous Idea: Evolution and the Meanings of Life. United States: Penguin Group.Dhillon, I. S., & Modha, D. S. (2001). Concept decompositions for large sparse text data using clustering. Machine learning, 42(1-2), 143-175. Dicke, W. M. (2004). Tales of a successful memeplex: How the water wars in the everglades were changed into a comprehensive plan. Knowledge, Technology & Policy, 16(4), 61-76. doi:10.1007/s12130-004-1015-2Ding, Y., Chowdhury, G. G., & Foo, S. (2001). Bibliometric cartography of information retrieval research by using co-word analysis. Information Processing and Management, 37, 817-842. Dobele, A., Lindgreen, A., Beverland, M., Vanhamme, J., & van Wijk, R. (2007). Why pass on viral messages? Because they connect emotionally. Business Horizons, 50(4), 291-304. doi:http://dx.doi.org/10.1016/j.bushor.2007.01.004Domingo, E. (2002). Quasispecies theory in virology. Journal of Virology, 76(1), 463-465. Domingo, E., Sheldon, J., & Perales, C. (2012). Viral quasispecies evolution. Microbiology and Molecular Biology Reviews, 76(2), 159-216. Duthie, A. B. (2003). A Letter on: The Fork and the Paperclip: A Memetic Perspective. Journal of Memetics - Evolutionary Models of Information Transmission, 8(1). Dutton, Y. C., & Heath, C. (2010). Cultural Evolution: Why are some cultural variants more successful than others? In M. Schaller, A. Norenzayan, S. J. Heine, T. Yamagishi, & T. Kameda (Eds.), Evolution, Culture and the Human Mind. United States of America: Taylor & Francis Group.Eadie, J. M., & Fryxell, J. M. (1992). Density Dependence, Frequency Dependence, and Alternative Nesting Strategies in Goldeneyes. The American Naturalist, 140(4), 621-641. Retrieved from http://www.jstor.org/stable/2462916Eberhardt, L. L. (1970). Correlation, Regression, and Density Dependence. Ecology, 51(2), 306-310. doi:10.2307/1933669Eigen, M. (1971). Self-organization of matter and the evolution of biological macromolecules. Naturwissenschaften, 58, 465-523. Eigen, M., & Schuster, P. (1977). A principle of natural self-organization. Naturwissenschaften, 64(11), 541-565. doi:10.1007/bf00450633Etzioni, O. (1996). The World-Wide Web: Quagmire or Gold Mine? Communications of the ACM, 39(11), 65-68. Eusuff, M., Lansey, K., & Pasha, F. (2006). Shuffled frog-leaping algorithm: a memetic meta-heuristic for discrete optimization. Engineering Optimization, 38(2), 129-154. doi:10.1080/03052150500384759Evans, N., & Levinson, S. C. (2009). The myth of language universals: Language diversity and its importance for cognitive science. Behavioral and Brain Sciences, 32(5), 429-448. doi:doi:10.1017/S0140525X0999094XEverett, D. (2005). Cultural Constraints on Grammar and Cognition in Pirahã: Another Look at the Design Features of Human Language. Current Anthropology, 46(4), 621-646. doi:10.1086/431525Fan, W., & Bifet, A. (2013). Mining big data: Current status, and forecast to the future. ACM SIGKDD Explorations Newsletter, 14(2), 1-5. doi:10.1145/2481244.2481246Feinerer, I., Hornik, K., & Meyer, D. (2008). Text Mining Infrastructure in R. Journal of Statistical Software, 25(5). Feldman, S. (1988). Structure and Consistency in Public Opinion: the Role of Core Beliefs and Values. American Journal of Political Science, 32(2), 416-440. Finkelstein, R., & Kruse, A. (2008). A Memetics Compendium. Briefing Report, DARPA Task Order CA-FIN-3212-024-08. Floridi, L. (2012). Big Data and Their Epistemological Challenge. Philosophy and Technology, 25(4), 435-437. doi:10.1007/s13347-012-0093-4Foster, K. R., Wenseleers, T., & Ratnieks, F. L. (2006). Kin selection is the key to altruism. Trends in Ecology & Evolution, 21(2), 57-60. Fox, D. R., & James, R.-S. (1995). Tests for Density Dependence Revisited. Oecologia, 103(4), 435-443. Retrieved from http://www.jstor.org/stable/4221057Gabora, L. (1997). The Origin and Evolution of Culture and Creativity. Journal of Memetics - Evolutionary Models of Information Transmission, 1(1). Gatherer, D. (1998). Why the "Thought Contagion` Metaphor is Retarding the Progress of Memetics. Journal of Memetics - Evolutionary Models of Information Transmission, 2(2). Gatherer, D. (2005). Finding a Niche for Memetics in the 21st Century. Journal of Memetics - Evolutionary Models of Information Transmission, 9(1). Gil-White, F. J. (2008). Let the meme be (a meme): Insisting too much on the genetic analogy will turn it into a straightjacket. In T. Botz-Bornstein (Ed.), Culture, Nature, Memes. Newcastle upon Tyne: Cambridge Scholars.Gill, J. (2012). An extra‐memetic empirical methodology to accompany theoretical memetics. International Journal of Organizational Analysis, 20(3), 323-336. doi:doi:10.1108/19348831211243839Gintis, H. (2007). A framework for the unification of the behavioral sciences. Behavioral and Brain Sciences, 30(1), 1-61. doi:10.1017/S0140525X07000581Glick, H. R., & Hays, S. P. (1991). Innovation and Reinvention in State Policymaking: Theory and the Evolution of Living Will Laws. The Journal of Polities, 53(3), 835-850. González-Bailón, S. (2013). Social Science in the Era of Big Data. Policy and Internet, 5(2), 147-160. Goodenough, O. R., & Dawkins, R. (1994). The `St Jude` mind virus. Nature, 371(6492), 23-24. Retrieved from http://dx.doi.org/10.1038/371023a0Gould, S. J. (1980). A Biological Homage to Mickey Mouse The Panda`s Thumb: More Reflections in Natural History. United States of America: W. W. Norton & Company.Grant, P. R., & Grant, B. R. (2009). The secondary contact phase of allopatric speciation in Darwin`s finches. PNAS, 106(48), 20141-20148. Gruhl, D., Guha, R., Liben-Nowell, D., & Tomkins, A. (2004). Information diffusion through blogspace. Paper presented at the Proceedings of the 13th international conference on World Wide Web.Guglielmino, C. R., Viganotti, C., Hewlett, B., & Cavalli-Sforza, L. L. (1995). Cultural variation in Africa: role of mechanisms of transmission and adaptation. Proceedings of the National Academy of Sciences, 92(16), 7585-7589. Retrieved from http://www.pnas.org/content/92/16/7585.abstractHahner, L. A. (2013). The Riot Kiss: Framing Memes as Visual Argument. Argumentation and Advocacy, 49(3), 151-166. Haig, D. (2007). Weismann rules! OK? Epigenetics and the Lamarckian temptation. Biol Philos, 22, 415-428. Hair, J. F., Black, W. C., Babin, B. J., Anderson, R. E., & Tatham, R. (2010). Multivariate data analysis (7th Eds.). NY: Pearson. Harrison, M. O., Koenig, H. G., Hays, J. C., Eme-Akwari, A. G., & Pargament, K. I. (2001). The epidemiology of religious coping: a review of recent literature. International Review of Psychiatry, 13(2), 86-93. doi:10.1080/09540260124356Hauser, M. D., Chomsky, N., & Fitch, W. T. (2002). The Faculty of Language: What Is It, Who Has It, and How Did It Evolve? Science, 298, 1569-1579. He, Q. (1999). Knowledge Discovery Through Co-Word Analysis. Library Trends, 48(1), 133-159. He, S., Zheng, X., & Zeng, D. (2016). A model-free scheme for meme ranking in social media. Decision Support Systems, 81, 1-11. doi:http://dx.doi.org/10.1016/j.dss.2015.10.002Heath, C., Bell, C., & Sternberg, E. (2001). Emotional selection in memes: The case of urban legends. Journal of Personality and Social Psychology, 81(6), 1028-1041. doi:citeulike-article-id:7657520doi: 10.1037/0022-3514.81.6.1028Henderson, P. A., & Southwood, T. R. E. (2016). Ecological Methods (4th ed.). Great Britain: John Wiley & Sones Ltd.Henrich, J., Boyd, R., & Richerson, P. (2008). Five Misunderstandings About Cultural Evolution. Human Nature, 19(2), 119-137. doi:10.1007/s12110-008-9037-1Herrando, P., xe, rez, S., Delean, S., Brook, B. W., & Bradshaw, C. J. A. (2012). Density dependence: an ecological Tower of Babel. Oecologia, 170(3), 585-603. Retrieved from http://www.jstor.org/stable/41686010Herring, S. C. (2010). Web Content Analysis: Expanding the Paradigm. In J. Hunsinger, L. Klastrup, & M. Allen (Eds.), International Handbook of Internet Research (pp. 233-249): Springer Netherlands.Heylighen, F., & Chielens, K. (2009). Cultural evolution and memetics. In B. Meyers (Ed.), Encyclopedia of complexity and system science.Hill, A. L., Rand, D. G., Nowak, M. A., & Christakis, N. A. (2010). Infectious Disease Modeling of Social Contagion in Networks. PLoS Computational Biology, 6(11), e1000968. doi:10.1371/journal.pcbi.1000968Hillebrandt, H. (2014). Pragmatic meta-compatibilism: compatibilism for social interactions and incompatibilism for public policy. A statistical formalization of the free will and moral responsibility problem using a multivariate generalized linear model approach. Hinde, R. A., & Barden, L. A. (1985). The evolution of the teddy bear. Animal Behaviour, 33(4), 1371-1373. Hodgson, G. M. (2005). Generalizing Darwinism to Social Evolution: Some Early Attempts. Journal of Economic Issues, 39(4), 899-914. Hodgson, G. M., & Knudsen, T. (2006). Dismantling Lamarckism: Why descriptions of socio-economic evolution as Lamarckian are misleading. Journal of Evolutionary Economics, 16(4), 343-366. doi:10.1007/s00191-006-0019-3Holm, T., Vuorisalo, T., & Sammalisto, K. (2014). Integrated management systems for enhancing education for sustainable development in universities: a memetic approach. Journal of Cleaner Production, Article in Press, 1-9. doi:http://dx.doi.org/10.1016/j.jclepro.2014.03.048Holyoak, M. (1994). Identifying Delayed Density Dependence in Time-Series Data. Oikos, 70(2), 296-304. doi:10.2307/3545641Honjo, K. (2004). Social epidemiology: Definition, history, and research examples. Environmental Health and Preventive Medicine, 9(5), 193-199. doi:10.1007/BF02898100Hoonlor, A., Szymanski, B. K., Zaki, M. J., & Chaoji, V. (2012). Document Clustering with Bursty Information. Computing and Informatics, 31, 1533-1555. Huang, A. (2008). Similarity Measures for Text Document Clustering. Paper presented at the Sixth New Zealand Computer Science Research Student Conference, Christchurch, New Zealan.Hull, D. L. (1982). The naked meme. In H. C. Plotkin (Ed.), Learning, Development, and Culture: Essays in evolutionary epistemology. United States of America: John Wiley & Sons Ltd.Hull, D. L. (2000). Taking memetics seriously: Memetics will be what we make it. In R. Aunger (Ed.), Darwinizing Culture: The Status of Memetics as a Science. United States: Oxford University Press.Hull, D. L. (2001). Science and Selection: Essays on biological evolution and the Philosophy of science. United States of America: Cambridge University Press.Hunt, G. R., & Gray, R. D. (2003). Diversification and cumulative evolution in New Caledonian crow tool manufacture. Proceedings of the Royal Society B: Biological Sciences, 270(1517), 867-874. doi:10.1098/rspb.2002.2302Inglehart, R., & Baker, W. E. (2000). Modernization, Cultural Change, and the Persistence of Traditional Values. American Sociological Review, 65(1), 19-51. Inglehart, R. F. (2008). Changing Values among Western Publics from 1970 to 2006. West European Politics, 31(1-2), 130-146. doi:10.1080/01402380701834747Ives, A. R., Abbott, K. C., & Ziebarth, N. L. (2010). Analysis of ecological time series with ARMA( p,q ) models. Ecology, 91(3), 858-871. Retrieved from http://www.jstor.org/stable/25661117Jørgensen, T. B., & Bozeman, B. (2007). Public Values: An Inventory. Administration & Society, 39(3), 354-381. Jacobs, F. M., Greenberg, D., Nguyen, N., Haeussler, M., Ewing, A. D., Katzman, S., . . . Haussler, D. (2014). An evolutionary arms race between KRAB zinc-finger genes ZNF91/93 and SVA/L1 retrotransposons. Nature, 516(7530), 242-245. Jan, S. (2003). The Evolution of a `Memeplex` in Late Mozart: Replicated Structures in Pamina`s `Ach ich fühl`s`. Journal of the Royal Musical Association, 128(2), 330-370. Retrieved from http://www.jstor.org/stable/3557501Janetzko, D. (2008). Nonreactive Data Collection on the Internet. In N. Fielding, R. M. Lee, & G. Blank (Eds.), The Sage Handbook of Online Research Methods. Singapore: SAGE Publications.Jantke, K. P., Fujima, J., Arnold, O., & Schulz, A. (2012). Memetic Communication Media: Concepts, Technologies, Applications. Paper presented at the 2012 IEEE International Conference on Multimedia and Expo Workshops. Janzen, D. H. (1971). Seed Predation by Animals. Annual Review of Ecology and Systematics, 2, 465-492. Retrieved from http://www.jstor.org/stable/2096937Jellal, M., & Wolff, F.-C. (2002). Cultural evolutionary altruism: theory and evidence. European Journal of Political Economy, 18(2), 241-262. doi:http://dx.doi.org/10.1016/S0176-2680(02)00079-4John, P. (1999). Ideas and interests; agendas and implementation: an evolutionary explanation of policy change in British local government finance. The British Journal of Politics & International Relations, 1(1), 39-62. doi:10.1111/1467-856X.00003John, P. (2003). Is There Life After Policy Streams, Advocacy Coalitions, and Punctuations: Using Evolutionary Theory to Explain Policy Change? Policy Studies Journal, 31(4), 481-498. doi:10.1111/1541-0072.00039Johnson, D. (2007). Mapping the Meme: A Geographical Approach to Materialist Rhetorical Criticism. Communication and Critical/Cultural Studies, 4(1), 27-50. doi:10.1080/14791420601138286Jones, B. D. (2003). Bounded Rationality and Political Science: Lessons from Public Administration and Public Policy. Journal of Public Administration Research and Theory, 13(4), 395-412. Kendall, J. R., & Laland, K. N. (2000). Mathematical Models for Memetics. Journal of Memetics - Evolutionary Models of Information Transmission, 1(4). Kerr, P. (2002). Saved from Extinction: Evolutionary Theorising, Politics and the State. The British Journal of Politics & International Relations, 4(2), 330-358. doi:10.1111/1467-856X.t01-1-00008Khanafiah, D., & Situngkir, H. (2004). Innovation as Evolution Case of Study: Phylomemetic of Cellphone Designs. Kilpinen, E. (2008). Memes versus signs: On the use of meaning concepts about nature and culture. Semiotica, 2008(171), 215-237. Kitchin, R. (2014). Big Data, new epistemologies and paradigm shifts. Big Data & Society, 1-12. doi:10.1177/2053951714528481Koenig, W. D., Mumme, R. L., Carmen, W. J., & Stanback, M. T. (1994). Acorn production by oaks in central coastal California: variation within and among years. Ecology, 75(1), 99-109. Kotsakos, D., Sakkos, P., Katakis, I., & Gunopulos, D. (2015). Language agnostic meme-filtering for hashtag-based social network analysis. Social Network Analysis and Mining, 5(1), 1-14. doi:10.1007/s13278-015-0271-3Krasnogor, N., & Gustafson, S. (2002). Toward Truly "Memetic" Memetic Algorithms: discussion and proofs of concept. Paper presented at the Advances in Nature-Inspired Computation: The PPSN VII Workshops. PEDAL (Parallel, Emergent and Distributed Architectures Lab).Kuhn, T., Perc, M., & Helbing, D. (2014). Inheritance patterns in citation networks reveal scientific memes. Physical Review X, 4(4). doi:http://dx.doi.org/10.2139/ssrn.2426903 Kuhn, T., Perc, M., & Helbing, D. (2014). Inheritance Patterns in Citation Networks Reveal Scientific Memes. Physical Review X, 4(4), 041036. Retrieved from http://link.aps.org/doi/10.1103/PhysRevX.4.041036Kutschera, U., & Niklas, K. J. (2004). The modern theory of biological evolution: an expanded synthesis. Naturwissenschaften, 91, 255-276. doi:10.1007/s00114-004-0515-yKvasnička, V., & Pospíchal, J. (2007). Artificial Chemistry and Replicator Theory of Coevolution of Genes and Memes. Collection of Czechoslovak Chemical Communication, 72(2), 223-251. Lai, T. L., & Wong, S. P.-S. (2006). Combining Domain Knowledge and Statistical Models in Time Series Analysis. Lecture Notes-Monograph Series, 52, 193-209. Retrieved from http://www.jstor.org/stable/20461438Laland, K. N., & Brown, G. R. (2002). Sense and Nonsense: Evolutionary perspectives on human behaviour. United Kingdom: Oxford University Press.Lande, R. (1976). Natural Selection and Random Genetic Drift in Phenotypic Evolution. Evolution, 30(2), 314-334. doi:10.2307/2407703Lang, A. L., & Barlow, J. C. (1997). Cultural Evolution in the Eurasian Tree Sparrow: Divergence between Introduced and Ancestral Populations. The Condor, 99(2), 413-423. doi:10.2307/1369948Lee, R. M. (2000). Unobtrusive Methods in Social Research. Great Britain: Open University Press.Leskovec, J., Backstrom, L., & Kleinberg, J. (2009). Meme-tracking and the dynamics of the news cycle. Paper presented at the Proceedings of the 15th ACM SIGKDD international conference on Knowledge discovery and data mining, Paris, France. Levy, D. A., & Nail, P. R. (1993). Contagion: A theoretical and empirical review and reconceptualization. Genetic, Social, and General Psychology Monographs, 119(2), 233-284. Lewis, O., & Steinmo, S. (2010). Taking evolution seriously in political science. Theory in Biosciences, 129(2-3), 235-245. doi:10.1007/s12064-010-0097-5Lewontin, R. C. (1982). Organism and environment. In H. C. Plotkin (Ed.), Learning, Development, and Culture: Essays in evolutionary epistemology. United States of America: John Wiley & Sons Ltd.Li, X., Luo, J., Chen, M.-R., & Wang, N. (2012). An improved shuffled frog-leaping algorithm with extremal optimisation for continuous optimisation. Information Sciences, 192(0), 143-151. doi:http://dx.doi.org/10.1016/j.ins.2010.07.016Lieberson, S. (2000). A Matter of Taste: How Names, Fashions, and Culture Change. United States of America: Yale University Press.Liu, T., Liu, S., Chen, Z., & Ma, W.-Y. (2003). An Evaluation on Feature Selection for Text Clustering. Paper presented at the Proceedings of the Twentieth International Conference on Machine Learning (ICML-2003), Washington DC.Lodge, M., & Wegrich, K. (2012). Public administration and executive politics: perennial questions in changing contexts. Public Policy and Administration, 27(3), 212-229. doi:10.1177/0952076712438724Lord, A., & Price, I. (2001). Reconstruction of organisational phylogeny from memetic similarity analysis: Proof of feasibility. Journal of Memetics - Evolutionary Models of Information Transmission, 5(2). Lustick, I. S. (2011). Taking Evolution Seriously: Historical Institutionalism and Evolutionary Theory. Polity, 43(2), 179-209. Lynch, A. (1996). The population memetics of birdsong. In D. E. Kroodsma & E. H. Miller (Eds.), Ecology and evolution of acoustic communication in birds: Comstock Publishing.Lyons, A., & Kashima, Y. (2003). How Are Stereotypes Maintained Through Communication? The Influence of Stereotype Sharedness. Journal of Personality and Social Psychology, 85(6), 989-1005. doi:10.1037/0022-3514.85.6.989Más, A., López-Galíndez, C., Cacho, I., Gómez, J., & Martínez, M. A. (2010). Unfinished Stories on Viral Quasispecies and Darwinian Views of Evolution. Journal of Molecular Biology, 397(4), 865-877. doi:http://dx.doi.org/10.1016/j.jmb.2010.02.005Majoros, W. (2002). Syntactic Structure in Birdsong: Memetic Evolution of Songs or Grammars? Journal of Memetics - Evolutionary Models of Information Transmission, 6(1). Mappes, T., Koivula, M., Koskela, E., Oksanen, T. A., Savolainen, T., & Sinervo, B. (2008). Frequency and density-dependent selection on life-history strategies–a field experiment. PLoS one, 3(2), e1687. Marsden, P. (1998). Memetics and Social Contagion: Two Sides of the Same Coin? Journal of Memetics - Evolutionary Models of Information Transmission, 2(2). Marsden, P. (2001). Is Suicide Contagious? A Case Study in Applied Memetics. Journal of Memetics - Evolutionary Models of Information Transmission, 5(1). Martin, J. L., & Wiley, J. A. (2000). Algebraic Representations of Beliefs and Attitudes Ii: Microbelief Models For Dichotomous Belief Data. Sociological Methodology, 30(1), 123-164. doi:10.1111/0081-1750.00077Massad, E., Rocha, A. F., Coutinho, F. A. B., & Lopez, L. F. (2013). Modelling the Spread of Memes: How Inovations are Transmitted from Brain to Brain. Applied Mathematical Sciences, 7(46), 2295-2306. May, R. M. (1973). Time-Delay Versus Stability in Population Models with Two and Three Trophic Levels. Ecology, 54(2), 315-325. doi:10.2307/1934339Maynard Smith, J. (1976). Group Selection. Quarterly Review of Biology, 51(2), 277-283. Mayr, E. (1982). Teleological and teleonomic: a new analysis. In H. C. Plotkin (Ed.), Learning, Development, and Culture: Essays in evolutionary epistemology. United States of America: John Wiley & Sons Ltd.McGlohon, M., Leskovec, J., Faloutsos, C., Hurst, M., & Glance, N. (2007). Finding Patterns in Blog Shapes and Blog Evolution. Paper presented at the International Conference on Weblogs and Social Media, Boulder, Colorado. McKelvey, K., Rudnick, A., Conover, M., & Menczer, F. (2012). Visualizing Communication on Social Media: Making Big Data Accessible. Paper presented at the Proc. 15th ACM Conference on Computer Supported Cooperative Work, Workshop on Collective Intelligence as Community Discourse and Action.Mesoudi, A. (2011). Cultural Evolution: How Darwinian Theory can explain human culture & synthesize the social sciences. United States of America: The University of Chicago Press.Mesoudi, A., Whiten, A., & Laland, K. N. (2006). Towards a unified science of cultural evolution. Behavioral and Brain Sciences, 29(4), 329-383. Misturelli, F., & Heffernan, C. (2012). The shape of change: A memetic analysis of the definitions of poverty from the 1970s to the 2000s. Journal of International Development, 24, S3-S18. doi:10.1002/jid.1770Mooney, C. Z., & Lee, M.-H. (1995). Legislative Morality in the American States: The Case of Pre-Roe Abortion Regulation Reform. American Journal of Political Science, 39(3), 599-627. Mooney, C. Z., & Lee, M.-H. (1999a). The Temporal Diffusion of Morality Policy: The Case of Death Penalty Legislation in the American States. Policy Studies Journal, 27(4), 766-780. doi:10.1111/j.1541-0072.1999.tb02002.xMooney, C. Z., & Lee, M.-H. (1999b). Morality Policy Reinvention: State Death Penalties. The ANNALS of the American Academy of Political and Social Science, 566, 80-92. Morris, R. F. (1959). Single-Factor Analysis in Population Dynamics. Ecology, 40(4), 580-588. doi:10.2307/1929811Moscato, P. (1989). On Evolution, Search, Optimization, Genetic Algorithms and Martial Arts: Towards Memetic Algorithms. Retrieved from Nagarajan, R., & Aruna, P. (2014). Document Clustering Using Co-word Analysis and Formation of Keyword Against Document Matrix. Journal of Theoretical and Applied Information Technology, 65(3), 831-838. Nelson, R. (2006). Evolutionary social science and universal Darwinism. Journal of Evolutionary Economics, 16(5), 491-510. doi:10.1007/s00191-006-0025-5Neri, F., Cotta, C., & Moscato, P. (2012). Preface. In F. Neri, C. Cotta, & P. Moscato (Eds.), Handbook of Memetic Algorithms: Springer-Verlag Berlin Heidelberg.Norenzayan, A., Schaller, M., & Heine, S. J. (2010). Introduction. In M. Schaller, A. Norenzayan, S. J. Heine, T. Yamagishi, & T. Kameda (Eds.), Evolution, Culture and the Human Mind. United States of America: Taylor & Francis Group.Norton, D. A., & Kelly, D. (1988). Mast Seeding Over 33 Years by Dacrydium cupressinum Lamb. (rimu) (Podocarpaceae) in New Zealand: The Importance of Economies of Scale. Functional Ecology, 2(3), 399-408. doi:10.2307/2389413Nye, B. D. (2014). Cognitive modeling of socially transmitted affordances: a computational model of behavioral adoption tested against archival data from the Stanford Prison Experiment. Computational and Mathematical Organization Theory, 20(3), 302-337. O`Brien, M. J., Lyman, R. L., Mesoudi, A., & VanPool, T. L. (2010). Cultural traits as units of analysis. Philosophical Transactions of the Royal Society B, 365, 3797-3806. O`Brien, M. J., & Shennan, S. J. (2010). Issues in Anthropological Studies of Innovation. In M. J. O`Brien & S. J. Shennan (Eds.), Innovation in Cultural Systems: Contributions from evolutionary anthropology. United States of America: Massachusetts Institute of Technology Press.O`Connor, B., Balasubramanya, R., Routledge, B. R., & Smith, N. A. (2010). From Tweets to Polls: Linking Text Sentiment to Public Opinion Time Series. Paper presented at the Proceedings of the Fourth International AAAI Conference on Weblogs and Social Media.O`Mahoney, J. (2007). The Diffusion of Management Innovations: The Possibilities and Limitations of Memetics. Journal of Management Studies, 44(8), 1324-1348. doi:10.1111/j.1467-6486.2007.00734.xOkasha, S. (2008). The units and levels of selection. In S. Sarkar & A. Plutynski (Eds.), A Companion to the Philosophy of Biology. Malden, MA: Blackwell Publishing.Oosterhout, C., Joyce, D. A., Cummings, S. M., Blais, J., Barson, N. J., Ramnarine, I. W., . . . Cable, J. (2006). Balancing selection, random genetic drift, and genetic variation at the major histocompatibility complex in two wild populations of guppies (Poecilia reticulata). Evolution, 60(12), 2562-2574. Page, B. I., & Shapiro, R. Y. (1983). Effects of Public Opinion on Policy. The American Political Science Review, 77(1), 175-190. Page, E. C. (2009). The Origins of Policy. In R. E. Goodin, M. Moran, & M. Rein (Eds.), The Oxford Handbook of Public Policy. United States: Oxford University Press.Pardo, L. M., MacKay, I., Oostra, B., van Duijn, C. M., & Aulchenko, Y. S. (2005). The effect of genetic drift in a young genetically isolated population. Annals of human genetics, 69(3), 288-295. Paull, J. (2009). Meme Maps: A Tool for Configuring Memes in Time and Space. European Journal of Scientific Research, 31(1), 11-18. Pearce, N. (1996). Traditional epidemiology, modern epidemiology, and public health. American Journal of Public Health, 86(5), 678-683. Retrieved from http://www.ncbi.nlm.nih.gov/pmc/articles/PMC1380476/Pemberton, H. E. (1936). The Curve of Culture Diffusion Rate. American Sociological Review, 1(4), 547-556. doi:10.2307/2084831Pemberton, H. E. (1937). The Effect of a Social Crisis on the Curve of Diffusion. American Sociological Review, 2(1), 55-61. doi:10.2307/2084565Penny, D. (2014). Cooperation and selfishness both occur during molecular evolution. Biology direct, 10(1), 26. Petroski, H. (1992). The Evolution of Useful Things: How Everyday Artifacts-From Forks and Pins to Paper Clips and Zippers-Came to be as they are (First Vintage Books ed.). United States of America: Vintage Books.Plotkin, H. C. (1982). Preface. In H. C. Plotkin (Ed.), Learning, Development, and Culture: Essays in evolutionary epistemology. United States of America: John Wiley & Sons Ltd.Plotkin, H. C. (2000). Culture and psychological mechanisms. In R. Aunger (Ed.), Darwinizing Culture: The Status of Memetics as a Science. United States: Oxford University Press.Pocklington, R., & Best, M. L. (1997). Cultural Evolution and Units of Selection in Replicating Text. Journal of Theoretical Biology, 188(1), 79-87. doi:http://dx.doi.org/10.1006/jtbi.1997.0460Podsakoff, P. M., MacKenzie, S. B., Lee, J.-Y., & Podsakoff, N. P. (2003). Common Method Biases in Behavioral Research: A Critical Review of the Literature and Recommended Remedies. Journal of Applied Psychology, 88(5), 879-903. Pollard, E., Lakhani, K. H., & Rothery, P. (1987). The Detection of Density-Dependence from a Series of Annual Censuses. Ecology, 68(6), 2046-2055. doi:10.2307/1939895Prentice, A. M., Hennig, B. J., & Fulford, A. (2008). Evolutionary origins of the obesity epidemic: natural selection of thrifty genes or genetic drift following predation release&quest. International journal of obesity, 32(11), 1607-1610. Raadschelders, J. C. N. (2011). The Future of the Study of Public Administration: Embedding Research Object and Methodology in Epistemology and Ontology. Public Administration Review, 71(6), 916-924. doi:10.1111/j.1540-6210.2011.02433.xRaadschelders, J. C. N., & Lee, K.-H. (2011). Trends in the Study of Public Administration: Empirical and Qualitative Observations from Public Administration Review, 2000–2009. Public Administration Review, 71(1), 19-33. doi:10.1111/j.1540-6210.2010.02303.xRanta, E., Lundberg, P., & Kaitala, V. (2006). Ecology of Populations. United States of America: Combridge University Press.Reader, S. M., & Laland, K. N. (1999). Do Animals Have Memes? Journal of Memetics - Evolutionary Models of Information Transmission, 3(2). Rice, R. E., & Rogers, E. M. (1980). Reinvention in the Innovation Process. Science Communication, 1(4), 499-514. Ritt, N. (2004). Selfish Sounds and Linguistic Evolution: A Darwinian Approach to Language Change. United Kingdom: Cambridge University Press.Rogers, E. M. (2003). Diffusion of Innovations (5th ed.). United States: Simon and Schuster.Romney, A. K., & Moore, C. C. (2001). Systemic Culture Patterns as Basic Units of Cultural Transmission and Evolution. Cross-Cultural Research, 35(2), 154-178. Runciman, W. G. (2005). Culture Does Evolve. History and Theory, 44(1), 1-13. Rutgers, M. R. (2010). Theory and Scope of Public Administration: An Introduction to the Study`s Epistemology. Public Administration Review, The Foundations of Public Administration Series. Sabatier, P. A. (2007). Theories of the policy process. United States: Westview Press.Santonja, F. J., Tarazona, A. C., & Villanueva, R. J. (2008). A mathematical model of the pressure of an extreme ideology on a society. Computers & Mathematics with Applications, 56(3), 836-846. doi:http://dx.doi.org/10.1016/j.camwa.2008.01.001Schaller, M., Conway Iii, L. G., & Tanchuk, T. L. (2002). Selective pressures on the once and future contents of ethnic stereotypes: Effects of the communicability of traits. Journal of Personality and Social Psychology, 82(6), 861-877. doi:10.1037/0022-3514.82.6.861Schuman, H., & Scott, J. (1987). Problems in the Use of Survey Questions to Measure Public Opinion. Science, New Series, 236(4804), 957-959. Shennan, S. (2008). Canoes and cultural evolution. PNAS, 105(9), 3175-3176. Shennan, S. (2011). Descent with modification and the archaeological record. Philosophical Transactions of the Royal Society of London B: Biological Sciences, 366(1567), 1070-1079. doi:10.1098/rstb.2010.0380Shepherd, J., & McKelvey, B. (2009). An empirical investigation of organizational memetic variation. Journal of Bioeconomics, 11(2), 135-164. doi:10.1007/s10818-009-9061-1Shifman, L. (2012). An anatomy of a YouTube meme. New Media and Society, 14(2), 187-203. doi:10.1177/1461444811412160Shifman, L. (2013). Memes in a Digital World: Reconciling with a Conceptual Troublemaker. Journal of Computer-Mediated Communication, 18(3), 362-377. doi:10.1111/jcc4.12013Shifman, L., & Thelwall, M. (2009). Assessing global diffusion with Web memetics: The spread and evolution of a popular joke. Journal of the American Society for Information Science and Technology, 60(12), 2567-2576. doi:10.1002/asi.21185Shumway, R. H., & Stoffer, D. S. (2011). Times Series Analysis and Its Applications: With R Examples (3rd ed.). United States of America: Springer Science+Business Media.Simmons, M. P., Adamic, L. A., & Adar, E. (2011). Memes Online: Extracted, Subtracted, Injected, and Recollected. Paper presented at the Proceedings of the Association for the Advancement of Artificial Intelligence (www.aaai.org).Simon, H. A. (1946). The Proverbs of Administration. Public Administration Review, 6(1), 53-67. Simon, H. A. (1947). A Comment on "The Science of Public Administration". Public Administration Review, 7(3), 200-203. Simon, H. A. (1990). A Mechanism for Social Selection and Successful Altruism. Science, 250, 1665-1668. Simon, H. A. (1998). Why Public Administration? Journal of Public Administration Research and Theory, 8(1), 1-11. Situngkir, H. (2004). On Selfish Memes: Culture as complex adaptive system. Journal of Social Complexity, 2(1), 20-32. Situngkir, H. (2008a). Conjectures to the Memes of Indonesian Songs. BFI Working Paper Series WP-VI-2008. Bandung Fe Institute. Situngkir, H. (2008b). Constructing the Phylomemetic Tree: Indonesian Tradition-Inspired Buildings. Bandung Fe Institute. Smith, F. E. (1961). Density dependence in the Australian thrips. Ecology, 42(2), 403-407. Sobkowicz, P., Kaschesky, M., & Bouchard, G. (2012). Opinion mining in social media: Modeling, simulating, and forecasting political opinions in the web. Government Information Quarterly, 29, 470-479. Solow, A. R. (1990). Testing for Density Dependence. A Cautionary Note. Oecologia, 83(1), 47-49. Retrieved from http://www.jstor.org/stable/4219294Sork, V. L., Bramble, J., & Sexton, O. (1993). Ecology of Mast-Fruiting in Three Species of North American Deciduous Oaks. Ecology, 74(2), 528-541. doi:10.2307/1939313Spasic, I., Ananiadou, S., McNaught, J., & Kumar, A. (2005). Text mining and ontologies in biomedicine: Making sense of raw text. Briefings in Bioinformatics, 6(3), 239-251. Speel, H.-C. (1995). Memetics: On a conceptual framework for cultural evolution. Paper presented at the Einstein Meets Magritte, Free University of Brussels. Speel, H.-C. (1997). A Memetic Analysis of Policy Making. Journal of Memetics - Evolutionary Models of Information Transmission, 1(2). Retrieved from http://cfpm.org/jom-emit/1997/vol1/speel_h-c.htmlSpitzberg, B. H. (2014). Toward A Model of Meme Diffusion (M3D). Communication Theory, 24(3), 311-339. doi:10.1111/comt.12042Stavrianou, A., Andritsos, P., & Nicoloyannis, N. (2007). Overview and semantic issues of text mining. ACM SIGMOD Record, 36(3), 23-34. doi:10.1145/1324185.1324190Steinmo, S. (2003). The evolution of policy ideas: tax policy in the 20th century. The British Journal of Politics & International Relations, 5(2), 206-236. doi:10.1111/1467-856X.00104Sterelny, K. (2006). Memes Revisited. The British Journal for the Philosophy of Science, 57(1), 145-165. doi:10.2307/3541656Strang, D., & Macy, M. W. (2001). In Search of Excellence: Fads, Success Stories, and Adaptive Emulation. American Journal of Sociology, 107(1), 147-182. doi:10.1086/323039Strehl, A., Ghosh, J., & Mooney, R. (2000). Impact of Similarity Measures on Web-page Clustering. Paper presented at the AAAI Workshop on AI for Web Search (AAAI 2000), Austin.Stylios, G., Christodoulakis, D., Besharat, J., Vonitsanou, M.-A., Kotrotsos, I., Koumpouri, A., & Stamou, S. (2010). Public Opinion Mining for Governmental Decisions. Electronic Journal of e-Government, 8(2), 203-214. Takahashi, Y., & Kawata, M. (2013). A comprehensive test for negative frequency-dependent selection. Population ecology, 55(3), 499-509. Tanner, J. T. (1966). Effects of Population Density on Growth Rates of Animal Populations. Ecology, 47(5), 733-745. doi:10.2307/1934260TechAmerica Foundation. (2012). Demystifying Big Data: A Practical Guide to Transforming the Business of Government Thelwall, M. (2006). Bloggers during the London attacks: Top information sources and topics. Paper presented at the Proc. of the World Wide Web 2006 Workshop on the Weblogging.Thelwall, M., Prabowo, R., & Fairclough, R. (2006). Are raw RSS feeds suitable for broad issue scanning? A science concern case study. Journal of the American Society for Information Science and Technology, 57(12), 1644-1654. Tornatzky, L. G., & Klein, K. J. (1982). Innovation Characteristics and Innovation Adoption-Implementation: A Meta-Analysis of Findings. IEEE Transactions on Engineering Management, 29(1), 28-43. Tseng, H., Chang, P.-C., Andrew, G., Jurafsky, D., & Manning, C. D. (2005). A Conditional Random Field Word Segmenter for Sighan Bakeoff 2005. Paper presented at the Fourth SIGHAN Workshop on Chinese Language Processing, Jeju Island.Turchin, P., & Taylor, A. D. (1992). Complex Dynamics in Ecological Time Series. Ecology, 73(1), 289-305. doi:10.2307/1938740Valente, T. W. (1996). Social network thresholds in the diffusion of innovations. Social networks, 18(1), 69-89. Van de Ven, A. H. (1986). Central Problems in the Management of Innovation. Management Science, 32(5), 590-607. Walker, J. L. (1969). The diffusion of innovations among the American states. American Political Science Review, 63(3), 880-899. Wang, F. L., Deng, X., & Zou, F. (2006). Towards Unified Chinese Segmentation Algorithm. Paper presented at the Proceedings of the 5th International Conference on Language Resources and Evaluation, LREC, Genoa.Wangersky, P. J., & Cunningham, W. J. (1957). Time Lag in Prey-Predator Population Models. Ecology, 38(1), 136-139. doi:10.2307/1932137Weiss, S. M., Indurkhya, N., Zhang, T., & Damerau, F. J. (2005). Text Mining: Predictive Methods for Analyzing Unstructured Information. United States of America: Springer Science+Business Media.Welzel, C., Inglehart, R., & Klingemann, H.-D. (2003). The theory of human development: A cross-cultural analysis. European Journal of Political Research, 42, 341-379. Weng, L., Flammini, A., Vespignani, A., & Menczer, F. (2012). Competition among memes in a world with limited attention. Scientific Reports, 2(335). West, S. A., Griffin, A. S., & Gardner, A. (2008). Social semantics: how useful has group selection been? Journal of Evolutionary Biology, 21(1), 374-385. Whetsell, T. A., & Shields, P. M. (2013). The Dynamics of Positivism in the Study of Public Administration: A Brief Intellectual History and Reappraisal. Administration & Society. doi:10.1177/0095399713490157Whittaker, J., Courtial, J.-P., & Law, J. (1989). Creativity and Conformity in Science: Titles, Keywords and Co-Word Analysis. Social Studies of Science, 19(3), 473-496. Retrieved from http://www.jstor.org/stable/285083Wiley, J. A., & Martin, J. L. (1999). Algebraic Representations of Beliefs and Attitudes: Partial Order Models for Item Responses. Sociological Methodology, 29(1), 113-146. doi:10.1111/0081-1750.00062Wilkins, J. S. (2001). The Appearance of Lamarckism in the Evolution of Culture. In J. Laurent & J. Nightingale (Eds.), Darwinism and Evolutionary Economics (pp. 160-183): Edward Elgar Pub.Williams, C. K., Ives, A. R., & Applegate, R. D. (2003). Population Dynamics across Geographical Ranges: Time-Series Analyses of Three Small Game Species. Ecology, 84(10), 2654-2667. Retrieved from http://www.jstor.org/stable/3450110Woiwod, I. P., & Hanski, I. (1992). Patterns of Density Dependence in Moths and Aphids. Journal of Animal Ecology, 61(3), 619-629. doi:10.2307/5617Wu, Y.-C., Yang, L.-W., Shen, J.-Y., Chen, L.-Y., & Wu, S.-T. (2008). Tornado in Multilingual Opinion Analysis: A Transductive Learning Approach for Chinese Sentimental Polarity Recognition. Paper presented at the Proceedings of NTCIR-7 Workshop Meeting, Tokyo, Japan.Wu, Z., & Tseng, G. (1993). Chinese text segmentation for text retrieval: Achievements and problems. Journal of the American Society for Information Science, 44(9), 532-542. doi:10.1002/(SICI)1097-4571(199310)44:9<532::AID-ASI3>3.0.CO;2-MYang, Q., & Wu, X. (2006). 10 Challenging Problems in Data Mining Research. International Journal of Information Technology & Decision Making, 5(4), 597-604. Yoon, S. (2008). Using memes and memetic processes to explain social and conceptual influences on student understanding about complex socio-scientific issues. Journal of Research in Science Teaching, 45(8), 900-921. doi:10.1002/tea.20256Yu, B., Kaufmann, S., & Diermeier, D. (2008). Exploring the characteristics of opinion expressions for political opinion classification. Paper presented at the Proceedings of the 2008 international conference on Digital government research, Montreal, Canada. Zalmanovitch, Y. (2014). Don`t reinvent the wheel: the search for an identity for public administration. International Review of Administrative Sciences. doi:10.1177/0020852314533456Zelazny, R. (1967). Lord of Light (First Eos trade paperback ed.). United States of America: Doubleday & Company.Zikopoulos, P. C., deRoos, D., Parasuraman, K., Deutsch, T., Corrigan, D., & Giles, J. (2013). Harness the Power of Big Data: The IBM Big Data Platform R. B. Melnyk (Ed.) Zikopoulos, P. C., Eaton, C., DeRoos, D., Deutsch, T., & Lapis, G. (2012). Understanding Big Data: Analytics for Enterprise Class Hadoop and Streaming Data S. Sit (Ed.) 描述 碩士
國立政治大學
公共行政學系
102256006資料來源 http://thesis.lib.nccu.edu.tw/record/#G0102256006 資料類型 thesis dc.contributor.advisor 蕭乃沂 zh_TW dc.contributor.advisor Hsiao, Naiyi en_US dc.contributor.author (Authors) 柯政豪 zh_TW dc.contributor.author (Authors) Ke, Cheng Hao en_US dc.creator (作者) 柯政豪 zh_TW dc.creator (作者) Ke, Cheng Hao en_US dc.date (日期) 2016 en_US dc.date.accessioned 11-Jul-2016 17:43:20 (UTC+8) - dc.date.available 11-Jul-2016 17:43:20 (UTC+8) - dc.date.issued (上傳時間) 11-Jul-2016 17:43:20 (UTC+8) - dc.identifier (Other Identifiers) G0102256006 en_US dc.identifier.uri (URI) http://nccur.lib.nccu.edu.tw/handle/140.119/98907 - dc.description (描述) 碩士 zh_TW dc.description (描述) 國立政治大學 zh_TW dc.description (描述) 公共行政學系 zh_TW dc.description (描述) 102256006 zh_TW dc.description.abstract (摘要) 公共行政學正面臨理論與方法無法結合的挑戰，這個問題在巨量資料的時代更是明顯，因為與人脫離的網路文本資料無法透過傳統的理論架構來解釋與分析，如果不引進新的本體論與認識論，公共行政學將遭遇無法深入分析巨量文本資料的困境。近代達爾文進化論因為透過複製者角度解釋自然界現象，所以能夠脫離以個別生物為核心的觀點，解釋過去無法分析的行為與動機。以進化論為基礎的模因學將社會文化的變化視為一種進化的過程，認為社會文化界的變化可以透過模因這種複製單位的進化來解釋，模因的觀點因為脫離以人為核心的角度，所以能夠解釋無法和使用者結合的網路文本資料。 本研究首先透過整合過去社會文化進化和模因學的研究，建構脫離使用者的巨量文本資料分析架構與假設，同時引入進化論與生態學中的方法與理論，驗證巨量網路文本背後的進化動態與機制。接著本研究針對Yahoo!奇摩新聞中探討「課綱微調」議題的1,761篇主文進行分析，透過中文斷詞與文本集群分析方法萃取出由不同模因類種建構的主文集群，並透過量化統計方法驗證個別集群文本特質與在時間上分布的趨勢對於整體主文集群變化的影響。結果發現個別模因類種本身在時間上的分布擁有密度依賴的關係，同時主文本身的情緒、字數等等特質，對產生的回文數也都有影響，但這些影響在不同密度的環境下會有所變化，網站版面環境本身也會與主文回文數有顯著的關係，而個別模因類種之間互動也都有顯著的正向交叉關係，另外模因類種也與詞彙組之間有顯著的正向和負向關係。 本研究的結果顯示以模因學探討巨量文本資料能夠允許研究者結合理論與文本探勘技術，以理論為出發點建構出能夠被驗證的假設，並引入進化論和生態學中的方法與架構進行資料的分析。研究發現由不同詞彙建構的文本數量在時間上的分布是一件必須觀察的現象，因為由類同詞彙建構的文本在過去時間點的變化，對於當下時間點類同主文的數量會有影響。同時文本特質和所處的網路環境也都是觀測網路文本變化時不可忽略的變數，因為這些因素對主文和回文的數量都有很重要的影響。另外分析網路文本時，應該以網站來區隔分析資料，因為網路環境同樣對於文本與回文的數量有影響。最後，出現在同一篇主文中機率高的詞彙組合也是會影響文本變化的重要因素之一。 本研究建議未來巨量文本資料的研究應該繼續以模因學的觀點出發，同時搭配具有不同優缺點的文本探勘技術與密度依賴檢定反覆驗證結果。未來的研究也宜朝向分析時間序列更長和出自不同網站的文本集，並建構能夠整合不同文本特質和環境影響的分析架構，另外納入文字以外的多媒體資料和以模因學角度設計的問卷調查資料進行探討。 zh_TW dc.description.abstract (摘要) The mismatch between theory and method is a crisis which the discipline of public administration cannot afford to ignore. The arrival of the “Era of Big Data”, only serves to make matters worse. As data becomes uncoupled with the individual, so goes any pretense of trying to provide analyses beyond that of mere description. If public administration refuses to import new ontology and epistemology, then very little could be gained from online text research. The Darwinian theory of evolution, ever since the Modern Synthesis, has embraced the replicator centered point of view when explaining all living phenomena. This has unshackled the theory from limitations of the traditional individual centered view of evolution. Memetics is a recent offshoot of the theory of evolution. It views social cultural change as a process based on the evolution of a cultural unit of selection, the meme. Due to memetics’ ability to explain social cultural evolution from the meme’s point of view, it is a natural candidate to examine the dynamics of “big” online text data. The first part of this research is on the construction of an online text analysis framework, with testable hypotheses, through the integration of past literature on evolution, social cultural evolution, memetics and ecology. The second part is concerned with the testing of the framework with empirical data. The text corpus used in this research contains 1,761 news reports from the Yahoo! News website on the issue of high school curriculum change. Chinese term segmentation and text clustering algorithms were applied to the corpus, in order to extract text quasi-species composed of similar memes. Statistical tests were then used to determine the influence of text characteristics and temporal distribution dynamics on the population of quasi-species. Findings indicate that the population dynamics of text quasi-species were influenced by density dependence. Text characteristics, such as word length and sentiment, also exert significant influence on the number of comments that each text receives. However, these influences are not equal under different density conditions. The location of the news articles within the website also creates a difference in the number of comments received. Finally, interactions between the temporal distribution of different quasi-species and between quasi-species and term groups also yielded significant positive and negative correlations. The results are proof that memetics is an ideal theoretical platform to connect theory with text mining/analysis methods. It allows for a theory based approach and the creation of testable hypotheses. Frameworks and methods based on evolution and ecological research are also applicable under memetics. The empirical findings point to the importance of monitoring the temporal distribution of online text, and the significance of text characteristics and website environments to text population changes. The results also illustrate the importance of term groups in the influence of text population dynamics. Together these variables and effects are all central to the understanding of the change in online text and comment numbers, and the effect of past text population on current population changes. Online texts from different websites should also be analyzed separately. This research recommends that future public administration big data analyses should continue to adopt the memetic approach. Nevertheless, attention should be given to the strengths and weaknesses of different text mining algorithms and density dependence tests. Big data time series from different websites and with longer temporal spans should also be considered, while social cultural artifacts other than texts should not be excluded from memetics based researches. New frameworks must also be constructed to integrate and understand, the interaction between important variables, such as, text characteristics and environmental influences. Findings on all forms of online data would also be enhanced through comparisons with results from questionnaires designed with memetics in mind. en_US dc.description.tableofcontents 第一章 緒論 3第一節 進化論與模因的簡介 5第二節 公共行政為什麼需要引入進化的概念 7第三節 目前巨量資料與網路民意的限制 12第四節 研究動機與目的 17第二章 文獻回顧 21第一節 近代達爾文進化論發展與概念 21第二節 模因學的發展與概念 40第三節 為何透過模因分析文本？ 61第三章 研究設計與方法 65第一節 網路文本的模因定義與測量 65第二節 網路文本資料 74第三節 研究流程與假設 80第四節 網路文本分析與演算法 86第五節 資料分析方法 95第四章 研究分析與結果 99第一節 斷詞與文本集群分析 100第二節 密度依賴選擇的影響 115第三節 文本特質的影響 130第四節 生態互動的影響 138第五節 環境的影響 143第六節 遺傳漂變的影響 147第七節 詞彙組的影響 151第八節 研究發現 169第五章 結論 179第一節 對於巨量資料分析的貢獻 180第二節 實務建議 183第三節 研究限制與後續研究建議 184參考文獻 187中文文獻 187英文文獻 187附錄1 211 zh_TW dc.format.extent 5254659 bytes - dc.format.mimetype application/pdf - dc.source.uri (資料來源) http://thesis.lib.nccu.edu.tw/record/#G0102256006 en_US dc.subject (關鍵詞) 文字探勘 zh_TW dc.subject (關鍵詞) 巨量資料 zh_TW dc.subject (關鍵詞) 模因學 zh_TW dc.subject (關鍵詞) 進化論 zh_TW dc.subject (關鍵詞) 生態學 zh_TW dc.subject (關鍵詞) Text Mining en_US dc.subject (關鍵詞) Big Data en_US dc.subject (關鍵詞) Memetics en_US dc.subject (關鍵詞) Darwinian Evolution en_US dc.subject (關鍵詞) Ecology en_US dc.title (題名) 巨量資料生態：以模因學分析網路文本的進化 zh_TW dc.title (題名) The Ecology of Big Data: A Memetic Approach on the Evolution of Online Text en_US dc.type (資料類型) thesis en_US dc.relation.reference (參考文獻) 李仲彬（2013a）。政府創新的類型與分佈：我國地方政府1999-2010年間的觀察。公共行政學報，44，73-112。李仲彬（2013b）。影響地方政府創新產出量的因素。東吳政治學報，31(1)，105-160。林千翔、張嘉惠、陳貞伶（2010）。結合長詞優先與序列標記之中文斷詞研究。中文計算語言學期刊(International Journal of Computational Linguistics and Chinese Language Processing)，15(3-4)，161-180。高婉瑜（2014）。網路語言的語音模因及其傳播—以宅女小紅的作品為例。淡江中文學報，30，277-315。陳良駒、張正宏、陳日鑫（2010）。以特徵詞共現特性探討知識管理研究議題相關性—使用共詞與關聯法則分析。資訊管理研究，17(4)，31-60。陳稼興、謝佳倫、許芳誠（2000）。以遺傳演算法為基礎的中文斷詞研究。資訊管理研究，2(2)，27-44。廖洲棚、陳敦源、蕭乃沂、廖興中（2014）。運用巨量資料實踐良善治理：網路民意導入政府決策分析之可行性研究。行政院研究發展考核委員會（編號：RDEC-MIS-102-003），未出版。蕭乃沂、陳敦源、廖洲棚（2015）。政府應用巨量資料精進公共服務與政策分析之可行性研究。國家發展委員會（編號：NDC-MIS-103-003），未出版。蕭乃沂、黃東益（2015）。104年度網路輿情蒐集、分析及運用計畫結案報告。教育部青年發展署，未出版。Adar, E., & Adamic, L. A. (2005, 19-22 Sept. 2005). Tracking information epidemics in blogspace. Paper presented at the 2005 IEEE/WIC/ACM International Conference on Web Intelligence, 2005. Proceedings.Adar, E., Teevan, J., & Dumais, S. T. (2009). Resonance on the web: web dynamics and revisitation patterns. Paper presented at the Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, Boston, MA, USA. Adar, E., Zhang, L., Adamic, L., & Lukose, R. (2004). Implicit structure and the dynamics of blogspace. Paper presented at the Workshop on the Weblogging Ecosystem, 13th International World Wide Web Conference Aggarwal, C. C., & Zhai, C. (2012). A Survey of Text Clustering Algorithms. In C. C. Aggarwal & C. Zhai (Eds.), Mining Text Data (pp. 77-128): Springer US.Akcora, C. G., Bayir, M. A., Demirbas, M., & Ferhatosmanoglu, H. (2010). Identifying breakpoints in public opinion. Paper presented at the Proceedings of the First Workshop on Social Media Analytics, Washington D.C., District of Columbia. Alford, J. R., & Hibbing, J. R. (2004). The Origin of Politics: An Evolutionary Theory of Political Behavior. Perspectives on Politics, 2(04), 707-723. doi:doi:10.1017/S1537592704040460Álvarez, A. (2005). Three Memetic Theories of Technology. Techné, 9(2). Amiri, B., Fathian, M., & Maroosi, A. (2009). Application of shuffled frog-leaping algorithm on clustering. The International Journal of Advanced Manufacturing Technology, 45(1-2), 199-209. doi:10.1007/s00170-009-1958-2Ansolabehere, S., & Hersh, E. (2012). Validation: What Big Data Reveal About Survey Misreporting and the Real Electorate. Political Analysis, 20(4), 437-459. doi:10.1093/pan/mps023Arpin, S. L., & Cushing, J. (2008). Modeling frequency-dependent selection with an application to cichlid fish. Math Biosci Eng, 5, 889-903. Astill, S. (2004). Equipping ourselves to explore the political Galapagos: ideas, networks and evolution. Paper presented at the York University Department of Politics at the Political Science Workshop. Aunger, R. (2000). Darwinizing Culture: The Status of Memetics as a Science. United States: Oxford University Press.Aunger, R. (2002). The Electric Meme: A New Theory of How We Think: Free Press.Aunger, R. (2006). What`s the matter with memes? In A. Grafen & M. Ridley (Eds.), Richard Dawkins: How a Scientist Changed the Way We Think. United Kingdom: Oxford University Press.Bail, C. A. (2014). The cultural environment: measuring culture with big data. Theory and Society, 43(3-4), 465-482. doi:10.1007/s11186-014-9216-5Baker, M. C., & Gammon, D. E. (2008). Vocal memes in natural populations of chickadees: why do some memes persist and others go extinct? Animal Behaviour, 75(1), 279-289. doi:http://dx.doi.org/10.1016/j.anbehav.2007.05.022Ball, P. (2004). Critical Mass: How one thing leads to another. United States of America: Farrar, Straus and Giroux.Bangerter, A., & Heath, C. (2004). The Mozart effect: Tracking the evolution of a scientific legend. British Journal of Social Psychology, 43(4), 605-623. doi:10.1348/0144666042565353Barbrook, A. C., Howe, C. J., Blake, N., & Robinson, P. (1998). The phylogeny of The Canterbury Tales. Nature, 394(6696), 839-839. Retrieved from http://dx.doi.org/10.1038/29667Bauckhage, C. (2011). Insights into Internet Memes. Paper presented at the Proceedings of the Fifth International AAAI Conference on Weblogs and Social Media.Beil, F., Ester, M., & Xu, X. (2002). Frequent term-based text clustering. Paper presented at the Proceedings of the eighth ACM SIGKDD international conference on Knowledge discovery and data mining, Edmonton, Alberta, Canada. Bentley, R. A. (2010). Fashion versus Reason in the Creative Industries. In M. J. O`Brien & S. J. Shennan (Eds.), Innovation in Cultural Systems: Contributions from evolutionary anthropology. United States of America: Massachusetts Institute of Technology Press.Benzon, W. (1996). Culture as an evolutionary arena. Journal of Social and Evolutionary Systems, 19(4), 321-362. doi:http://dx.doi.org/10.1016/S1061-7361(96)90003-XBest, M. L. (1997). Models for Interacting Populations of Memes: Competition and Niche Behavior. Journal of Memetics - Evolutionary Models of Information Transmission, 1(2). Best, M. L. (1997b). An ecology of text: using text retrieval to study alife on the net. Artificial Life, 3(4), 261-287. Bettencourt, L. M. A., Cintrón-Arias, A., Kaiser, D. I., & Castillo-Chávez, C. (2006). The power of a good idea: Quantitative modeling of the spread of ideas from epidemiological models. Physica A: Statistical Mechanics and its Applications, 364, 513-536. doi:http://dx.doi.org/10.1016/j.physa.2005.08.083Bikhchandani, S., Hirshleifer, D., & Welch, I. (1992). A Theory of Fads, Fashion, Custom, and Cultural Change as Informational Cascades. Journal of Political Economy, 100(5), 992-1026. Retrieved from http://www.jstor.org/stable/2138632Bjørnstad, O. N., Ims, R. A., & Lambin, X. (1999). Spatial population dynamics: analyzing patterns and processes of population synchrony. Trends in Ecology & Evolution, 14(11), 427-432. Bjarneskans, H., Grønnevik, B., & Sandberg, A. (1997). The Lifecycle of Memes. http://www.aleph.se/Trans/Cultural/Memetics/memecycle.html Retrieved from http://www.aleph.se/Trans/Cultural/Memetics/memecycle.htmlBlackmore, S. (1999). The Meme Machine. United States: Oxford University Press Inc.Blackmore, S. (2000). The memes` eye view. In R. Aunger (Ed.), Darwinizing Culture: The Status of Memetics as a Science. United States: Oxford University Press.Blackmore, S. (2001). Evolution and Memes: The Human Brain as a Selective Imitation Device. Cybernetics and Systems: An International Journal, 32, 225-255. Blackmore, S. (2003). Consciousness in Meme Machines. Journal of Consciousness Studies, 10(4-5), 19-30. Retrieved from http://www.ingentaconnect.com/content/imp/jcs/2003/00000010/F0020004/1344Bleay, C., Comendant, T., & Sinervo, B. (2007). An experimental test of frequency-dependent selection on male mating strategy in the field. Proceedings of the Royal Society of London B: Biological Sciences, 274(1621), 2019-2025. Blute, M. (1979). Sociocultural evolutionism: An untried theory. Behavioral Science, 24(1), 46-59. doi:10.1002/bs.3830240107Blute, M. (2005). Memetics and evolutionary social science. Journal of Memetics - Evolutionary Models of Information Transmission, 9(1). Blute, M. (2010). Darwinian Sociocultural Evolution: Solutions to dilemmas in cultural and social theory. United States of America: Cambridge University Press.Borenstein, E. (2004). Survival of the Catchiest: Memes and Postmodern Russia. The Slavic and East European Journal, 48(3), 462-483. doi:10.2307/3220071Boushey, G. (2010). Policy Diffusion Dynamics in America. United States: Cambridge University Press.Boyd, D., & Crawford, K. (2012). Critical Questions for Big Data. Information, Communication & Society, 15(5), 662-679. doi:10.1080/1369118X.2012.678878Boyne, G. A. (1996). The Intellectual Crisis in British Public Administration: Is Public Management the Problem or the Solution? Public Administration, 74(4), 679-694. doi:10.1111/j.1467-9299.1996.tb00890.xBrook, B. W., & Bradshaw, C. J. A. (2006). Strength of Evidence for Density Dependence in Abundance Time Series of 1198 Species. Ecology, 87(6), 1445-1451. Retrieved from http://www.jstor.org/stable/20069094Bull, L., Holland, O., & Blackmore, S. (2000). On meme-gene coevolution. Artificial Life, 6(3), 227-235. doi:10.1162/106454600568852Bulmer, M. G. (1975). The Statistical Analysis of Density Dependence. Biometrics, 31(4), 901-911. doi:10.2307/2529815Burgess, J. (2008). All Your Chocolate Rain Are Belong to Us?` Viral Video, YouTube and the Dynamics of Participatory Culture. In G. Lovink & R. S. Miles (Eds.), The VideoVortex Reader: Responses to YouTube. Amsterdam: Institute of Network Cultures.Burt, R. S. (1987). Social contagion and innovation: Cohesion versus structural equivalence. American Journal of Sociology, 1287-1335. Buss, D. M., Shackelford, T. K., Kirkpatrick, L. A., & Larsen, R. J. (2001). A Half Century of Mate Preferences: The Cultural Evolution of Values. Journal of Marriage and Family, 63(2), 491-503. doi:10.2307/3654608Butts, C. T., & Hilgeman, C. (2003). Inferring Potential Memetic Structure from Cross-Sectional Data: An Application to American Religious Beliefs. Journal of Memetics - Evolutionary Models of Information Transmission, 1(7). Calsbeek, R., Bonvini, L., & Cox, R. M. (2010). Geographic Variation, Frequency-Dependent Selection, and the Maintenance of a Female-Limited Polymorphism. Evolution, 64(1), 116-125. Retrieved from http://www.jstor.org/stable/27743496Cambria, E., Schuller, B. r., Yunqing, X., & Havasi, C. (2013). New Avenues in Opinion Mining and Sentiment Analysis. Intelligent Systems, IEEE, 28(2), 15-21. doi:10.1109/MIS.2013.30Campbell, D. T. (1960). Blind Variation and Selective Retention in Creative Thought as in Other Knowledge Processes. Psychological Review, 67(6), 380-400. Campbell, D. T. (1979). Comments on the sociobiology of ethics and moralizing. Behavioral Science, 24(1), 37-45. Campbell, D. T. (1982). Evolutionary epistemology. In H. C. Plotkin (Ed.), Learning, Development, and Culture: Essays in evolutionary epistemology. United States of America: John Wiley & Sons Ltd.Castelfranchi, C. (2001). Towards a Cognitive Memetics: Socio-Cognitive Mechanisms for Memes Selection and Spreading. Journal of Memetics - Evolutionary Models of Information Transmission, 5(1). Cavalli-Sforza, L. L., & Feldman, M. W. (1981). Cultural Transmission and Evolution: A Quantitative Approach. United Kingdom: Princeton University Press.Cenettlsr, H., & McGill, P. (1996). Random genetic drift in the female germline explains the rapid segregation of mammalian mitochondrial DNA. Nature genetics, 14. Centers for Disease Control and Prevention. (2012). Principles of Epidemiology in Public Health Practice Chang, P.-C., Galley, M., & Manning, C. D. (2008). Optimizing Chinese word segmentation for machine translation performance. Paper presented at the Proceedings of the Third Workshop on Statistical Machine Translation, Columbus, Ohio. Chatfield, C. (1996). The Analysis of Time Series: An Introduction (5th ed.). Great Britain: Chapman & Hall.Chen, C. L. P., & Zhang, C.-Y. (2014). Data-intensive applications, challenges, techniques and technologies: A survey on Big Data. Information Sciences, In Press, Corrected Proof. Chen, M., Mao, S., & Liu, Y. (2014). Big Data: A Survey. Mobile Networks and Applications, 19(2), 171-209. doi:10.1007/s11036-013-0489-0Chiang, T.-H., Chang, J.-S., Lin, M.-Y., & Su, K.-Y. (1992). Statistical Models for Word Segmentation and Unknown Word Resolution. Paper presented at the 5th R.O.C. Computational Linguistics Conference. Chick, G. (2001). Culture-Bearing Units and the Units of Culture: An Introduction. Cross-Cultural Research, 35(2), 91-108. Chielens, K., & Heylighen, F. (2005). Operationalization of Meme Selection Criteria: Methodologies to Empirically Test Memetic Predictions. Paper presented at the Joint Symposium on Socially Inspired Computing Chielens, K., & Heylighen, F. (2005). Operationalization of meme selection criteria: Methodologies to empirically test memetic predictions. Proceedings of the Joint Symposium on Socially Inspired Computing (AISB’05), 14–20. doi:citeulike-article-id:8877404Coker, C. (2008). War, Memes and Memeplexes. International Affairs (Royal Institute of International Affairs 1944-), 84(5), 903-914. doi:10.2307/25144927Colbaugh, R., & Glass, K. (2012). Early warning analysis for social diffusion events. Security Informatics, 1(18). doi:10.1109/ISI.2010.5484778Collins, A., Hart, E. M., & Molofsky, J. (2010). Differential response to frequency-dependent interactions: an experimental test using genotypes of an invasive grass. Oecologia, 164(4), 959-969. doi:10.1007/s00442-010-1719-9Connell, J. H., & Green, P. T. (2000). Seedling Dynamics over Thirty-Two Years in a Tropical Rain Forest Tree. Ecology, 81(2), 568-584. doi:10.2307/177449Conte, R. (2000). Memes through (social) minds. In R. Aunger (Ed.), Darwinizing Culture: The Status of Memetics as a Science. United States: Oxford University Press.Corley, C. D., Cook, D. J., Mikler, A. R., & Singh, K. P. (2010). Text and structural data mining of influenza mentions in web and social media. International journal of environmental research and public health, 7(2), 596-615. Cowpertwait, P. S. P., & Metcalfe, A. V. (2009). Introductory Time Series with R. United States of America: Springer Science+Business Media.Crawford, K., Miltner, K., & Gray, M. L. (2014). Critiquing Big Data: Politics, Ethics, Epistemology. International Journal of Communication, 8, 1663-1672. Cryer, J. D., & Chan, K.-S. (2008). Time Series Analysis: With Applications in R (2nd ed.). United States of America: Springer Science+Business Media, LLC.Csikszentmihalyi, M. (1993). The Evolving Self: A psychology for the third millennium. United States of America: HarperCollins Publishers, Inc.Cumbley, R., & Church, P. (2013). Is “Big Data” creepy? Computer Law & Security Review, 29(5), 601-609. doi:http://dx.doi.org/10.1016/j.clsr.2013.07.007Dale, M. R. T., & Fortin, M.-J. (2002). Spatial autocorrelation and statistical tests in ecology. Écoscience, 9(2), 162-167. Retrieved from http://www.jstor.org/stable/42901480Daley, D. J., & Kendall, D. G. (1965). Stochastic Rumours. IMA Journal of Applied Mathematics, 1(1), 42-55. doi:10.1093/imamat/1.1.42Damanpour, F. (1991). Organizational Innovation: A Meta-Analysis of Effects of Determinants and Moderators. The Academy of Management Journal, 34(3), 555-590. doi:10.2307/256406Davis, C. B. (2007). Cultural Evolution and Performance Genres: Memetics in Theatre History and Performance Studies. Theatre Journal, 59(4), 595-614. Dawkins, R. (1976). The Selfish Gene (30th anniversary ed.). United States: Oxford University Press Inc.Dawkins, R. (1982). The Extended Phenotype: The long reach of the gene. United States of America: Oxford University Press.de Jong, M. (1999). Survival of the institutionally fittest concepts. Journal of Memetics - Evolutionary Models of Information Transmission, 3(1). De Tiége, A., Tanghe, K., Braeckman, J., & Van de Peer, Y. (2014). From DNA- to NA-centrism and the conditions for gene-centrism revisited. Biol Philos, 29(55-69). doi:10.1007/s10539-013-9393-zDennett, D. C. (1991). Consciousness Explained. United States of America: Little, Brown & Company.Dennett, D. C. (1995). Darwin`s Dangerous Idea: Evolution and the Meanings of Life. United States: Penguin Group.Dhillon, I. S., & Modha, D. S. (2001). Concept decompositions for large sparse text data using clustering. Machine learning, 42(1-2), 143-175. Dicke, W. M. (2004). Tales of a successful memeplex: How the water wars in the everglades were changed into a comprehensive plan. Knowledge, Technology & Policy, 16(4), 61-76. doi:10.1007/s12130-004-1015-2Ding, Y., Chowdhury, G. G., & Foo, S. (2001). Bibliometric cartography of information retrieval research by using co-word analysis. Information Processing and Management, 37, 817-842. Dobele, A., Lindgreen, A., Beverland, M., Vanhamme, J., & van Wijk, R. (2007). Why pass on viral messages? Because they connect emotionally. Business Horizons, 50(4), 291-304. doi:http://dx.doi.org/10.1016/j.bushor.2007.01.004Domingo, E. (2002). Quasispecies theory in virology. Journal of Virology, 76(1), 463-465. Domingo, E., Sheldon, J., & Perales, C. (2012). Viral quasispecies evolution. Microbiology and Molecular Biology Reviews, 76(2), 159-216. Duthie, A. B. (2003). A Letter on: The Fork and the Paperclip: A Memetic Perspective. Journal of Memetics - Evolutionary Models of Information Transmission, 8(1). Dutton, Y. C., & Heath, C. (2010). Cultural Evolution: Why are some cultural variants more successful than others? In M. Schaller, A. Norenzayan, S. J. Heine, T. Yamagishi, & T. Kameda (Eds.), Evolution, Culture and the Human Mind. United States of America: Taylor & Francis Group.Eadie, J. M., & Fryxell, J. M. (1992). Density Dependence, Frequency Dependence, and Alternative Nesting Strategies in Goldeneyes. The American Naturalist, 140(4), 621-641. Retrieved from http://www.jstor.org/stable/2462916Eberhardt, L. L. (1970). Correlation, Regression, and Density Dependence. Ecology, 51(2), 306-310. doi:10.2307/1933669Eigen, M. (1971). Self-organization of matter and the evolution of biological macromolecules. Naturwissenschaften, 58, 465-523. Eigen, M., & Schuster, P. (1977). A principle of natural self-organization. Naturwissenschaften, 64(11), 541-565. doi:10.1007/bf00450633Etzioni, O. (1996). The World-Wide Web: Quagmire or Gold Mine? Communications of the ACM, 39(11), 65-68. Eusuff, M., Lansey, K., & Pasha, F. (2006). Shuffled frog-leaping algorithm: a memetic meta-heuristic for discrete optimization. Engineering Optimization, 38(2), 129-154. doi:10.1080/03052150500384759Evans, N., & Levinson, S. C. (2009). The myth of language universals: Language diversity and its importance for cognitive science. Behavioral and Brain Sciences, 32(5), 429-448. doi:doi:10.1017/S0140525X0999094XEverett, D. (2005). Cultural Constraints on Grammar and Cognition in Pirahã: Another Look at the Design Features of Human Language. Current Anthropology, 46(4), 621-646. doi:10.1086/431525Fan, W., & Bifet, A. (2013). Mining big data: Current status, and forecast to the future. ACM SIGKDD Explorations Newsletter, 14(2), 1-5. doi:10.1145/2481244.2481246Feinerer, I., Hornik, K., & Meyer, D. (2008). Text Mining Infrastructure in R. Journal of Statistical Software, 25(5). Feldman, S. (1988). Structure and Consistency in Public Opinion: the Role of Core Beliefs and Values. American Journal of Political Science, 32(2), 416-440. Finkelstein, R., & Kruse, A. (2008). A Memetics Compendium. Briefing Report, DARPA Task Order CA-FIN-3212-024-08. Floridi, L. (2012). Big Data and Their Epistemological Challenge. Philosophy and Technology, 25(4), 435-437. doi:10.1007/s13347-012-0093-4Foster, K. R., Wenseleers, T., & Ratnieks, F. L. (2006). Kin selection is the key to altruism. Trends in Ecology & Evolution, 21(2), 57-60. Fox, D. R., & James, R.-S. (1995). Tests for Density Dependence Revisited. Oecologia, 103(4), 435-443. Retrieved from http://www.jstor.org/stable/4221057Gabora, L. (1997). The Origin and Evolution of Culture and Creativity. Journal of Memetics - Evolutionary Models of Information Transmission, 1(1). Gatherer, D. (1998). Why the "Thought Contagion` Metaphor is Retarding the Progress of Memetics. Journal of Memetics - Evolutionary Models of Information Transmission, 2(2). Gatherer, D. (2005). Finding a Niche for Memetics in the 21st Century. Journal of Memetics - Evolutionary Models of Information Transmission, 9(1). Gil-White, F. J. (2008). Let the meme be (a meme): Insisting too much on the genetic analogy will turn it into a straightjacket. In T. Botz-Bornstein (Ed.), Culture, Nature, Memes. Newcastle upon Tyne: Cambridge Scholars.Gill, J. (2012). An extra‐memetic empirical methodology to accompany theoretical memetics. International Journal of Organizational Analysis, 20(3), 323-336. doi:doi:10.1108/19348831211243839Gintis, H. (2007). A framework for the unification of the behavioral sciences. Behavioral and Brain Sciences, 30(1), 1-61. doi:10.1017/S0140525X07000581Glick, H. R., & Hays, S. P. (1991). Innovation and Reinvention in State Policymaking: Theory and the Evolution of Living Will Laws. The Journal of Polities, 53(3), 835-850. González-Bailón, S. (2013). Social Science in the Era of Big Data. Policy and Internet, 5(2), 147-160. Goodenough, O. R., & Dawkins, R. (1994). The `St Jude` mind virus. Nature, 371(6492), 23-24. Retrieved from http://dx.doi.org/10.1038/371023a0Gould, S. J. (1980). A Biological Homage to Mickey Mouse The Panda`s Thumb: More Reflections in Natural History. United States of America: W. W. Norton & Company.Grant, P. R., & Grant, B. R. (2009). The secondary contact phase of allopatric speciation in Darwin`s finches. PNAS, 106(48), 20141-20148. Gruhl, D., Guha, R., Liben-Nowell, D., & Tomkins, A. (2004). Information diffusion through blogspace. Paper presented at the Proceedings of the 13th international conference on World Wide Web.Guglielmino, C. R., Viganotti, C., Hewlett, B., & Cavalli-Sforza, L. L. (1995). Cultural variation in Africa: role of mechanisms of transmission and adaptation. Proceedings of the National Academy of Sciences, 92(16), 7585-7589. Retrieved from http://www.pnas.org/content/92/16/7585.abstractHahner, L. A. (2013). The Riot Kiss: Framing Memes as Visual Argument. Argumentation and Advocacy, 49(3), 151-166. Haig, D. (2007). Weismann rules! OK? Epigenetics and the Lamarckian temptation. Biol Philos, 22, 415-428. Hair, J. F., Black, W. C., Babin, B. J., Anderson, R. E., & Tatham, R. (2010). Multivariate data analysis (7th Eds.). NY: Pearson. Harrison, M. O., Koenig, H. G., Hays, J. C., Eme-Akwari, A. G., & Pargament, K. I. (2001). The epidemiology of religious coping: a review of recent literature. International Review of Psychiatry, 13(2), 86-93. doi:10.1080/09540260124356Hauser, M. D., Chomsky, N., & Fitch, W. T. (2002). The Faculty of Language: What Is It, Who Has It, and How Did It Evolve? Science, 298, 1569-1579. He, Q. (1999). Knowledge Discovery Through Co-Word Analysis. Library Trends, 48(1), 133-159. He, S., Zheng, X., & Zeng, D. (2016). A model-free scheme for meme ranking in social media. Decision Support Systems, 81, 1-11. doi:http://dx.doi.org/10.1016/j.dss.2015.10.002Heath, C., Bell, C., & Sternberg, E. (2001). Emotional selection in memes: The case of urban legends. Journal of Personality and Social Psychology, 81(6), 1028-1041. doi:citeulike-article-id:7657520doi: 10.1037/0022-3514.81.6.1028Henderson, P. A., & Southwood, T. R. E. (2016). Ecological Methods (4th ed.). Great Britain: John Wiley & Sones Ltd.Henrich, J., Boyd, R., & Richerson, P. (2008). Five Misunderstandings About Cultural Evolution. Human Nature, 19(2), 119-137. doi:10.1007/s12110-008-9037-1Herrando, P., xe, rez, S., Delean, S., Brook, B. W., & Bradshaw, C. J. A. (2012). Density dependence: an ecological Tower of Babel. Oecologia, 170(3), 585-603. Retrieved from http://www.jstor.org/stable/41686010Herring, S. C. (2010). Web Content Analysis: Expanding the Paradigm. In J. Hunsinger, L. Klastrup, & M. Allen (Eds.), International Handbook of Internet Research (pp. 233-249): Springer Netherlands.Heylighen, F., & Chielens, K. (2009). Cultural evolution and memetics. In B. Meyers (Ed.), Encyclopedia of complexity and system science.Hill, A. L., Rand, D. G., Nowak, M. A., & Christakis, N. A. (2010). Infectious Disease Modeling of Social Contagion in Networks. PLoS Computational Biology, 6(11), e1000968. doi:10.1371/journal.pcbi.1000968Hillebrandt, H. (2014). Pragmatic meta-compatibilism: compatibilism for social interactions and incompatibilism for public policy. A statistical formalization of the free will and moral responsibility problem using a multivariate generalized linear model approach. Hinde, R. A., & Barden, L. A. (1985). The evolution of the teddy bear. Animal Behaviour, 33(4), 1371-1373. Hodgson, G. M. (2005). Generalizing Darwinism to Social Evolution: Some Early Attempts. Journal of Economic Issues, 39(4), 899-914. Hodgson, G. M., & Knudsen, T. (2006). Dismantling Lamarckism: Why descriptions of socio-economic evolution as Lamarckian are misleading. Journal of Evolutionary Economics, 16(4), 343-366. doi:10.1007/s00191-006-0019-3Holm, T., Vuorisalo, T., & Sammalisto, K. (2014). Integrated management systems for enhancing education for sustainable development in universities: a memetic approach. Journal of Cleaner Production, Article in Press, 1-9. doi:http://dx.doi.org/10.1016/j.jclepro.2014.03.048Holyoak, M. (1994). Identifying Delayed Density Dependence in Time-Series Data. Oikos, 70(2), 296-304. doi:10.2307/3545641Honjo, K. (2004). Social epidemiology: Definition, history, and research examples. Environmental Health and Preventive Medicine, 9(5), 193-199. doi:10.1007/BF02898100Hoonlor, A., Szymanski, B. K., Zaki, M. J., & Chaoji, V. (2012). Document Clustering with Bursty Information. Computing and Informatics, 31, 1533-1555. Huang, A. (2008). Similarity Measures for Text Document Clustering. Paper presented at the Sixth New Zealand Computer Science Research Student Conference, Christchurch, New Zealan.Hull, D. L. (1982). The naked meme. In H. C. Plotkin (Ed.), Learning, Development, and Culture: Essays in evolutionary epistemology. United States of America: John Wiley & Sons Ltd.Hull, D. L. (2000). Taking memetics seriously: Memetics will be what we make it. In R. Aunger (Ed.), Darwinizing Culture: The Status of Memetics as a Science. United States: Oxford University Press.Hull, D. L. (2001). Science and Selection: Essays on biological evolution and the Philosophy of science. United States of America: Cambridge University Press.Hunt, G. R., & Gray, R. D. (2003). Diversification and cumulative evolution in New Caledonian crow tool manufacture. Proceedings of the Royal Society B: Biological Sciences, 270(1517), 867-874. doi:10.1098/rspb.2002.2302Inglehart, R., & Baker, W. E. (2000). Modernization, Cultural Change, and the Persistence of Traditional Values. American Sociological Review, 65(1), 19-51. Inglehart, R. F. (2008). Changing Values among Western Publics from 1970 to 2006. West European Politics, 31(1-2), 130-146. doi:10.1080/01402380701834747Ives, A. R., Abbott, K. C., & Ziebarth, N. L. (2010). Analysis of ecological time series with ARMA( p,q ) models. Ecology, 91(3), 858-871. Retrieved from http://www.jstor.org/stable/25661117Jørgensen, T. B., & Bozeman, B. (2007). Public Values: An Inventory. Administration & Society, 39(3), 354-381. Jacobs, F. M., Greenberg, D., Nguyen, N., Haeussler, M., Ewing, A. D., Katzman, S., . . . Haussler, D. (2014). An evolutionary arms race between KRAB zinc-finger genes ZNF91/93 and SVA/L1 retrotransposons. Nature, 516(7530), 242-245. Jan, S. (2003). The Evolution of a `Memeplex` in Late Mozart: Replicated Structures in Pamina`s `Ach ich fühl`s`. Journal of the Royal Musical Association, 128(2), 330-370. Retrieved from http://www.jstor.org/stable/3557501Janetzko, D. (2008). Nonreactive Data Collection on the Internet. In N. Fielding, R. M. Lee, & G. Blank (Eds.), The Sage Handbook of Online Research Methods. Singapore: SAGE Publications.Jantke, K. P., Fujima, J., Arnold, O., & Schulz, A. (2012). Memetic Communication Media: Concepts, Technologies, Applications. Paper presented at the 2012 IEEE International Conference on Multimedia and Expo Workshops. Janzen, D. H. (1971). Seed Predation by Animals. Annual Review of Ecology and Systematics, 2, 465-492. Retrieved from http://www.jstor.org/stable/2096937Jellal, M., & Wolff, F.-C. (2002). Cultural evolutionary altruism: theory and evidence. European Journal of Political Economy, 18(2), 241-262. doi:http://dx.doi.org/10.1016/S0176-2680(02)00079-4John, P. (1999). Ideas and interests; agendas and implementation: an evolutionary explanation of policy change in British local government finance. The British Journal of Politics & International Relations, 1(1), 39-62. doi:10.1111/1467-856X.00003John, P. (2003). Is There Life After Policy Streams, Advocacy Coalitions, and Punctuations: Using Evolutionary Theory to Explain Policy Change? Policy Studies Journal, 31(4), 481-498. doi:10.1111/1541-0072.00039Johnson, D. (2007). Mapping the Meme: A Geographical Approach to Materialist Rhetorical Criticism. Communication and Critical/Cultural Studies, 4(1), 27-50. doi:10.1080/14791420601138286Jones, B. D. (2003). Bounded Rationality and Political Science: Lessons from Public Administration and Public Policy. Journal of Public Administration Research and Theory, 13(4), 395-412. Kendall, J. R., & Laland, K. N. (2000). Mathematical Models for Memetics. Journal of Memetics - Evolutionary Models of Information Transmission, 1(4). Kerr, P. (2002). Saved from Extinction: Evolutionary Theorising, Politics and the State. The British Journal of Politics & International Relations, 4(2), 330-358. doi:10.1111/1467-856X.t01-1-00008Khanafiah, D., & Situngkir, H. (2004). Innovation as Evolution Case of Study: Phylomemetic of Cellphone Designs. Kilpinen, E. (2008). Memes versus signs: On the use of meaning concepts about nature and culture. Semiotica, 2008(171), 215-237. Kitchin, R. (2014). Big Data, new epistemologies and paradigm shifts. Big Data & Society, 1-12. doi:10.1177/2053951714528481Koenig, W. D., Mumme, R. L., Carmen, W. J., & Stanback, M. T. (1994). Acorn production by oaks in central coastal California: variation within and among years. Ecology, 75(1), 99-109. Kotsakos, D., Sakkos, P., Katakis, I., & Gunopulos, D. (2015). Language agnostic meme-filtering for hashtag-based social network analysis. Social Network Analysis and Mining, 5(1), 1-14. doi:10.1007/s13278-015-0271-3Krasnogor, N., & Gustafson, S. (2002). Toward Truly "Memetic" Memetic Algorithms: discussion and proofs of concept. Paper presented at the Advances in Nature-Inspired Computation: The PPSN VII Workshops. PEDAL (Parallel, Emergent and Distributed Architectures Lab).Kuhn, T., Perc, M., & Helbing, D. (2014). Inheritance patterns in citation networks reveal scientific memes. Physical Review X, 4(4). doi:http://dx.doi.org/10.2139/ssrn.2426903 Kuhn, T., Perc, M., & Helbing, D. (2014). Inheritance Patterns in Citation Networks Reveal Scientific Memes. Physical Review X, 4(4), 041036. Retrieved from http://link.aps.org/doi/10.1103/PhysRevX.4.041036Kutschera, U., & Niklas, K. J. (2004). The modern theory of biological evolution: an expanded synthesis. Naturwissenschaften, 91, 255-276. doi:10.1007/s00114-004-0515-yKvasnička, V., & Pospíchal, J. (2007). Artificial Chemistry and Replicator Theory of Coevolution of Genes and Memes. Collection of Czechoslovak Chemical Communication, 72(2), 223-251. Lai, T. L., & Wong, S. P.-S. (2006). Combining Domain Knowledge and Statistical Models in Time Series Analysis. Lecture Notes-Monograph Series, 52, 193-209. Retrieved from http://www.jstor.org/stable/20461438Laland, K. N., & Brown, G. R. (2002). Sense and Nonsense: Evolutionary perspectives on human behaviour. United Kingdom: Oxford University Press.Lande, R. (1976). Natural Selection and Random Genetic Drift in Phenotypic Evolution. Evolution, 30(2), 314-334. doi:10.2307/2407703Lang, A. L., & Barlow, J. C. (1997). Cultural Evolution in the Eurasian Tree Sparrow: Divergence between Introduced and Ancestral Populations. The Condor, 99(2), 413-423. doi:10.2307/1369948Lee, R. M. (2000). Unobtrusive Methods in Social Research. Great Britain: Open University Press.Leskovec, J., Backstrom, L., & Kleinberg, J. (2009). Meme-tracking and the dynamics of the news cycle. Paper presented at the Proceedings of the 15th ACM SIGKDD international conference on Knowledge discovery and data mining, Paris, France. Levy, D. A., & Nail, P. R. (1993). Contagion: A theoretical and empirical review and reconceptualization. Genetic, Social, and General Psychology Monographs, 119(2), 233-284. Lewis, O., & Steinmo, S. (2010). Taking evolution seriously in political science. Theory in Biosciences, 129(2-3), 235-245. doi:10.1007/s12064-010-0097-5Lewontin, R. C. (1982). Organism and environment. In H. C. Plotkin (Ed.), Learning, Development, and Culture: Essays in evolutionary epistemology. United States of America: John Wiley & Sons Ltd.Li, X., Luo, J., Chen, M.-R., & Wang, N. (2012). An improved shuffled frog-leaping algorithm with extremal optimisation for continuous optimisation. Information Sciences, 192(0), 143-151. doi:http://dx.doi.org/10.1016/j.ins.2010.07.016Lieberson, S. (2000). A Matter of Taste: How Names, Fashions, and Culture Change. United States of America: Yale University Press.Liu, T., Liu, S., Chen, Z., & Ma, W.-Y. (2003). An Evaluation on Feature Selection for Text Clustering. Paper presented at the Proceedings of the Twentieth International Conference on Machine Learning (ICML-2003), Washington DC.Lodge, M., & Wegrich, K. (2012). Public administration and executive politics: perennial questions in changing contexts. Public Policy and Administration, 27(3), 212-229. doi:10.1177/0952076712438724Lord, A., & Price, I. (2001). Reconstruction of organisational phylogeny from memetic similarity analysis: Proof of feasibility. Journal of Memetics - Evolutionary Models of Information Transmission, 5(2). Lustick, I. S. (2011). Taking Evolution Seriously: Historical Institutionalism and Evolutionary Theory. Polity, 43(2), 179-209. Lynch, A. (1996). The population memetics of birdsong. In D. E. Kroodsma & E. H. Miller (Eds.), Ecology and evolution of acoustic communication in birds: Comstock Publishing.Lyons, A., & Kashima, Y. (2003). How Are Stereotypes Maintained Through Communication? The Influence of Stereotype Sharedness. Journal of Personality and Social Psychology, 85(6), 989-1005. doi:10.1037/0022-3514.85.6.989Más, A., López-Galíndez, C., Cacho, I., Gómez, J., & Martínez, M. A. (2010). Unfinished Stories on Viral Quasispecies and Darwinian Views of Evolution. Journal of Molecular Biology, 397(4), 865-877. doi:http://dx.doi.org/10.1016/j.jmb.2010.02.005Majoros, W. (2002). Syntactic Structure in Birdsong: Memetic Evolution of Songs or Grammars? Journal of Memetics - Evolutionary Models of Information Transmission, 6(1). Mappes, T., Koivula, M., Koskela, E., Oksanen, T. A., Savolainen, T., & Sinervo, B. (2008). Frequency and density-dependent selection on life-history strategies–a field experiment. PLoS one, 3(2), e1687. Marsden, P. (1998). Memetics and Social Contagion: Two Sides of the Same Coin? Journal of Memetics - Evolutionary Models of Information Transmission, 2(2). Marsden, P. (2001). Is Suicide Contagious? A Case Study in Applied Memetics. Journal of Memetics - Evolutionary Models of Information Transmission, 5(1). Martin, J. L., & Wiley, J. A. (2000). Algebraic Representations of Beliefs and Attitudes Ii: Microbelief Models For Dichotomous Belief Data. Sociological Methodology, 30(1), 123-164. doi:10.1111/0081-1750.00077Massad, E., Rocha, A. F., Coutinho, F. A. B., & Lopez, L. F. (2013). Modelling the Spread of Memes: How Inovations are Transmitted from Brain to Brain. Applied Mathematical Sciences, 7(46), 2295-2306. May, R. M. (1973). Time-Delay Versus Stability in Population Models with Two and Three Trophic Levels. Ecology, 54(2), 315-325. doi:10.2307/1934339Maynard Smith, J. (1976). Group Selection. Quarterly Review of Biology, 51(2), 277-283. Mayr, E. (1982). Teleological and teleonomic: a new analysis. In H. C. Plotkin (Ed.), Learning, Development, and Culture: Essays in evolutionary epistemology. United States of America: John Wiley & Sons Ltd.McGlohon, M., Leskovec, J., Faloutsos, C., Hurst, M., & Glance, N. (2007). Finding Patterns in Blog Shapes and Blog Evolution. Paper presented at the International Conference on Weblogs and Social Media, Boulder, Colorado. McKelvey, K., Rudnick, A., Conover, M., & Menczer, F. (2012). Visualizing Communication on Social Media: Making Big Data Accessible. Paper presented at the Proc. 15th ACM Conference on Computer Supported Cooperative Work, Workshop on Collective Intelligence as Community Discourse and Action.Mesoudi, A. (2011). Cultural Evolution: How Darwinian Theory can explain human culture & synthesize the social sciences. United States of America: The University of Chicago Press.Mesoudi, A., Whiten, A., & Laland, K. N. (2006). Towards a unified science of cultural evolution. Behavioral and Brain Sciences, 29(4), 329-383. Misturelli, F., & Heffernan, C. (2012). The shape of change: A memetic analysis of the definitions of poverty from the 1970s to the 2000s. Journal of International Development, 24, S3-S18. doi:10.1002/jid.1770Mooney, C. Z., & Lee, M.-H. (1995). Legislative Morality in the American States: The Case of Pre-Roe Abortion Regulation Reform. American Journal of Political Science, 39(3), 599-627. Mooney, C. Z., & Lee, M.-H. (1999a). The Temporal Diffusion of Morality Policy: The Case of Death Penalty Legislation in the American States. Policy Studies Journal, 27(4), 766-780. doi:10.1111/j.1541-0072.1999.tb02002.xMooney, C. Z., & Lee, M.-H. (1999b). Morality Policy Reinvention: State Death Penalties. The ANNALS of the American Academy of Political and Social Science, 566, 80-92. Morris, R. F. (1959). Single-Factor Analysis in Population Dynamics. Ecology, 40(4), 580-588. doi:10.2307/1929811Moscato, P. (1989). On Evolution, Search, Optimization, Genetic Algorithms and Martial Arts: Towards Memetic Algorithms. Retrieved from Nagarajan, R., & Aruna, P. (2014). Document Clustering Using Co-word Analysis and Formation of Keyword Against Document Matrix. Journal of Theoretical and Applied Information Technology, 65(3), 831-838. Nelson, R. (2006). Evolutionary social science and universal Darwinism. Journal of Evolutionary Economics, 16(5), 491-510. doi:10.1007/s00191-006-0025-5Neri, F., Cotta, C., & Moscato, P. (2012). Preface. In F. Neri, C. Cotta, & P. Moscato (Eds.), Handbook of Memetic Algorithms: Springer-Verlag Berlin Heidelberg.Norenzayan, A., Schaller, M., & Heine, S. J. (2010). Introduction. In M. Schaller, A. Norenzayan, S. J. Heine, T. Yamagishi, & T. Kameda (Eds.), Evolution, Culture and the Human Mind. United States of America: Taylor & Francis Group.Norton, D. A., & Kelly, D. (1988). Mast Seeding Over 33 Years by Dacrydium cupressinum Lamb. (rimu) (Podocarpaceae) in New Zealand: The Importance of Economies of Scale. Functional Ecology, 2(3), 399-408. doi:10.2307/2389413Nye, B. D. (2014). Cognitive modeling of socially transmitted affordances: a computational model of behavioral adoption tested against archival data from the Stanford Prison Experiment. Computational and Mathematical Organization Theory, 20(3), 302-337. O`Brien, M. J., Lyman, R. L., Mesoudi, A., & VanPool, T. L. (2010). Cultural traits as units of analysis. Philosophical Transactions of the Royal Society B, 365, 3797-3806. O`Brien, M. J., & Shennan, S. J. (2010). Issues in Anthropological Studies of Innovation. In M. J. O`Brien & S. J. Shennan (Eds.), Innovation in Cultural Systems: Contributions from evolutionary anthropology. United States of America: Massachusetts Institute of Technology Press.O`Connor, B., Balasubramanya, R., Routledge, B. R., & Smith, N. A. (2010). From Tweets to Polls: Linking Text Sentiment to Public Opinion Time Series. Paper presented at the Proceedings of the Fourth International AAAI Conference on Weblogs and Social Media.O`Mahoney, J. (2007). The Diffusion of Management Innovations: The Possibilities and Limitations of Memetics. Journal of Management Studies, 44(8), 1324-1348. doi:10.1111/j.1467-6486.2007.00734.xOkasha, S. (2008). The units and levels of selection. In S. Sarkar & A. Plutynski (Eds.), A Companion to the Philosophy of Biology. Malden, MA: Blackwell Publishing.Oosterhout, C., Joyce, D. A., Cummings, S. M., Blais, J., Barson, N. J., Ramnarine, I. W., . . . Cable, J. (2006). Balancing selection, random genetic drift, and genetic variation at the major histocompatibility complex in two wild populations of guppies (Poecilia reticulata). Evolution, 60(12), 2562-2574. Page, B. I., & Shapiro, R. Y. (1983). Effects of Public Opinion on Policy. The American Political Science Review, 77(1), 175-190. Page, E. C. (2009). The Origins of Policy. In R. E. Goodin, M. Moran, & M. Rein (Eds.), The Oxford Handbook of Public Policy. United States: Oxford University Press.Pardo, L. M., MacKay, I., Oostra, B., van Duijn, C. M., & Aulchenko, Y. S. (2005). The effect of genetic drift in a young genetically isolated population. Annals of human genetics, 69(3), 288-295. Paull, J. (2009). Meme Maps: A Tool for Configuring Memes in Time and Space. European Journal of Scientific Research, 31(1), 11-18. Pearce, N. (1996). Traditional epidemiology, modern epidemiology, and public health. American Journal of Public Health, 86(5), 678-683. Retrieved from http://www.ncbi.nlm.nih.gov/pmc/articles/PMC1380476/Pemberton, H. E. (1936). The Curve of Culture Diffusion Rate. American Sociological Review, 1(4), 547-556. doi:10.2307/2084831Pemberton, H. E. (1937). The Effect of a Social Crisis on the Curve of Diffusion. American Sociological Review, 2(1), 55-61. doi:10.2307/2084565Penny, D. (2014). Cooperation and selfishness both occur during molecular evolution. Biology direct, 10(1), 26. Petroski, H. (1992). The Evolution of Useful Things: How Everyday Artifacts-From Forks and Pins to Paper Clips and Zippers-Came to be as they are (First Vintage Books ed.). United States of America: Vintage Books.Plotkin, H. C. (1982). Preface. In H. C. Plotkin (Ed.), Learning, Development, and Culture: Essays in evolutionary epistemology. United States of America: John Wiley & Sons Ltd.Plotkin, H. C. (2000). Culture and psychological mechanisms. In R. Aunger (Ed.), Darwinizing Culture: The Status of Memetics as a Science. United States: Oxford University Press.Pocklington, R., & Best, M. L. (1997). Cultural Evolution and Units of Selection in Replicating Text. Journal of Theoretical Biology, 188(1), 79-87. doi:http://dx.doi.org/10.1006/jtbi.1997.0460Podsakoff, P. M., MacKenzie, S. B., Lee, J.-Y., & Podsakoff, N. P. (2003). Common Method Biases in Behavioral Research: A Critical Review of the Literature and Recommended Remedies. Journal of Applied Psychology, 88(5), 879-903. Pollard, E., Lakhani, K. H., & Rothery, P. (1987). The Detection of Density-Dependence from a Series of Annual Censuses. Ecology, 68(6), 2046-2055. doi:10.2307/1939895Prentice, A. M., Hennig, B. J., & Fulford, A. (2008). Evolutionary origins of the obesity epidemic: natural selection of thrifty genes or genetic drift following predation release&quest. International journal of obesity, 32(11), 1607-1610. Raadschelders, J. C. N. (2011). The Future of the Study of Public Administration: Embedding Research Object and Methodology in Epistemology and Ontology. Public Administration Review, 71(6), 916-924. doi:10.1111/j.1540-6210.2011.02433.xRaadschelders, J. C. N., & Lee, K.-H. (2011). Trends in the Study of Public Administration: Empirical and Qualitative Observations from Public Administration Review, 2000–2009. Public Administration Review, 71(1), 19-33. doi:10.1111/j.1540-6210.2010.02303.xRanta, E., Lundberg, P., & Kaitala, V. (2006). Ecology of Populations. United States of America: Combridge University Press.Reader, S. M., & Laland, K. N. (1999). Do Animals Have Memes? Journal of Memetics - Evolutionary Models of Information Transmission, 3(2). Rice, R. E., & Rogers, E. M. (1980). Reinvention in the Innovation Process. Science Communication, 1(4), 499-514. Ritt, N. (2004). Selfish Sounds and Linguistic Evolution: A Darwinian Approach to Language Change. United Kingdom: Cambridge University Press.Rogers, E. M. (2003). Diffusion of Innovations (5th ed.). United States: Simon and Schuster.Romney, A. K., & Moore, C. C. (2001). Systemic Culture Patterns as Basic Units of Cultural Transmission and Evolution. Cross-Cultural Research, 35(2), 154-178. Runciman, W. G. (2005). Culture Does Evolve. History and Theory, 44(1), 1-13. Rutgers, M. R. (2010). Theory and Scope of Public Administration: An Introduction to the Study`s Epistemology. Public Administration Review, The Foundations of Public Administration Series. Sabatier, P. A. (2007). Theories of the policy process. United States: Westview Press.Santonja, F. J., Tarazona, A. C., & Villanueva, R. J. (2008). A mathematical model of the pressure of an extreme ideology on a society. Computers & Mathematics with Applications, 56(3), 836-846. doi:http://dx.doi.org/10.1016/j.camwa.2008.01.001Schaller, M., Conway Iii, L. G., & Tanchuk, T. L. (2002). Selective pressures on the once and future contents of ethnic stereotypes: Effects of the communicability of traits. Journal of Personality and Social Psychology, 82(6), 861-877. doi:10.1037/0022-3514.82.6.861Schuman, H., & Scott, J. (1987). Problems in the Use of Survey Questions to Measure Public Opinion. Science, New Series, 236(4804), 957-959. Shennan, S. (2008). Canoes and cultural evolution. PNAS, 105(9), 3175-3176. Shennan, S. (2011). Descent with modification and the archaeological record. Philosophical Transactions of the Royal Society of London B: Biological Sciences, 366(1567), 1070-1079. doi:10.1098/rstb.2010.0380Shepherd, J., & McKelvey, B. (2009). An empirical investigation of organizational memetic variation. Journal of Bioeconomics, 11(2), 135-164. doi:10.1007/s10818-009-9061-1Shifman, L. (2012). An anatomy of a YouTube meme. New Media and Society, 14(2), 187-203. doi:10.1177/1461444811412160Shifman, L. (2013). Memes in a Digital World: Reconciling with a Conceptual Troublemaker. Journal of Computer-Mediated Communication, 18(3), 362-377. doi:10.1111/jcc4.12013Shifman, L., & Thelwall, M. (2009). Assessing global diffusion with Web memetics: The spread and evolution of a popular joke. Journal of the American Society for Information Science and Technology, 60(12), 2567-2576. doi:10.1002/asi.21185Shumway, R. H., & Stoffer, D. S. (2011). Times Series Analysis and Its Applications: With R Examples (3rd ed.). United States of America: Springer Science+Business Media.Simmons, M. P., Adamic, L. A., & Adar, E. (2011). Memes Online: Extracted, Subtracted, Injected, and Recollected. Paper presented at the Proceedings of the Association for the Advancement of Artificial Intelligence (www.aaai.org).Simon, H. A. (1946). The Proverbs of Administration. Public Administration Review, 6(1), 53-67. Simon, H. A. (1947). A Comment on "The Science of Public Administration". Public Administration Review, 7(3), 200-203. Simon, H. A. (1990). A Mechanism for Social Selection and Successful Altruism. Science, 250, 1665-1668. Simon, H. A. (1998). Why Public Administration? Journal of Public Administration Research and Theory, 8(1), 1-11. Situngkir, H. (2004). On Selfish Memes: Culture as complex adaptive system. Journal of Social Complexity, 2(1), 20-32. Situngkir, H. (2008a). Conjectures to the Memes of Indonesian Songs. BFI Working Paper Series WP-VI-2008. Bandung Fe Institute. Situngkir, H. (2008b). Constructing the Phylomemetic Tree: Indonesian Tradition-Inspired Buildings. Bandung Fe Institute. Smith, F. E. (1961). Density dependence in the Australian thrips. Ecology, 42(2), 403-407. Sobkowicz, P., Kaschesky, M., & Bouchard, G. (2012). Opinion mining in social media: Modeling, simulating, and forecasting political opinions in the web. Government Information Quarterly, 29, 470-479. Solow, A. R. (1990). Testing for Density Dependence. A Cautionary Note. Oecologia, 83(1), 47-49. Retrieved from http://www.jstor.org/stable/4219294Sork, V. L., Bramble, J., & Sexton, O. (1993). Ecology of Mast-Fruiting in Three Species of North American Deciduous Oaks. Ecology, 74(2), 528-541. doi:10.2307/1939313Spasic, I., Ananiadou, S., McNaught, J., & Kumar, A. (2005). Text mining and ontologies in biomedicine: Making sense of raw text. Briefings in Bioinformatics, 6(3), 239-251. Speel, H.-C. (1995). Memetics: On a conceptual framework for cultural evolution. Paper presented at the Einstein Meets Magritte, Free University of Brussels. Speel, H.-C. (1997). A Memetic Analysis of Policy Making. Journal of Memetics - Evolutionary Models of Information Transmission, 1(2). Retrieved from http://cfpm.org/jom-emit/1997/vol1/speel_h-c.htmlSpitzberg, B. H. (2014). Toward A Model of Meme Diffusion (M3D). Communication Theory, 24(3), 311-339. doi:10.1111/comt.12042Stavrianou, A., Andritsos, P., & Nicoloyannis, N. (2007). Overview and semantic issues of text mining. ACM SIGMOD Record, 36(3), 23-34. doi:10.1145/1324185.1324190Steinmo, S. (2003). The evolution of policy ideas: tax policy in the 20th century. The British Journal of Politics & International Relations, 5(2), 206-236. doi:10.1111/1467-856X.00104Sterelny, K. (2006). Memes Revisited. The British Journal for the Philosophy of Science, 57(1), 145-165. doi:10.2307/3541656Strang, D., & Macy, M. W. (2001). In Search of Excellence: Fads, Success Stories, and Adaptive Emulation. American Journal of Sociology, 107(1), 147-182. doi:10.1086/323039Strehl, A., Ghosh, J., & Mooney, R. (2000). Impact of Similarity Measures on Web-page Clustering. Paper presented at the AAAI Workshop on AI for Web Search (AAAI 2000), Austin.Stylios, G., Christodoulakis, D., Besharat, J., Vonitsanou, M.-A., Kotrotsos, I., Koumpouri, A., & Stamou, S. (2010). Public Opinion Mining for Governmental Decisions. Electronic Journal of e-Government, 8(2), 203-214. Takahashi, Y., & Kawata, M. (2013). A comprehensive test for negative frequency-dependent selection. Population ecology, 55(3), 499-509. Tanner, J. T. (1966). Effects of Population Density on Growth Rates of Animal Populations. Ecology, 47(5), 733-745. doi:10.2307/1934260TechAmerica Foundation. (2012). Demystifying Big Data: A Practical Guide to Transforming the Business of Government Thelwall, M. (2006). Bloggers during the London attacks: Top information sources and topics. Paper presented at the Proc. of the World Wide Web 2006 Workshop on the Weblogging.Thelwall, M., Prabowo, R., & Fairclough, R. (2006). Are raw RSS feeds suitable for broad issue scanning? A science concern case study. Journal of the American Society for Information Science and Technology, 57(12), 1644-1654. Tornatzky, L. G., & Klein, K. J. (1982). Innovation Characteristics and Innovation Adoption-Implementation: A Meta-Analysis of Findings. IEEE Transactions on Engineering Management, 29(1), 28-43. Tseng, H., Chang, P.-C., Andrew, G., Jurafsky, D., & Manning, C. D. (2005). A Conditional Random Field Word Segmenter for Sighan Bakeoff 2005. Paper presented at the Fourth SIGHAN Workshop on Chinese Language Processing, Jeju Island.Turchin, P., & Taylor, A. D. (1992). Complex Dynamics in Ecological Time Series. Ecology, 73(1), 289-305. doi:10.2307/1938740Valente, T. W. (1996). Social network thresholds in the diffusion of innovations. Social networks, 18(1), 69-89. Van de Ven, A. H. (1986). Central Problems in the Management of Innovation. Management Science, 32(5), 590-607. Walker, J. L. (1969). The diffusion of innovations among the American states. American Political Science Review, 63(3), 880-899. Wang, F. L., Deng, X., & Zou, F. (2006). Towards Unified Chinese Segmentation Algorithm. Paper presented at the Proceedings of the 5th International Conference on Language Resources and Evaluation, LREC, Genoa.Wangersky, P. J., & Cunningham, W. J. (1957). Time Lag in Prey-Predator Population Models. Ecology, 38(1), 136-139. doi:10.2307/1932137Weiss, S. M., Indurkhya, N., Zhang, T., & Damerau, F. J. (2005). Text Mining: Predictive Methods for Analyzing Unstructured Information. United States of America: Springer Science+Business Media.Welzel, C., Inglehart, R., & Klingemann, H.-D. (2003). The theory of human development: A cross-cultural analysis. European Journal of Political Research, 42, 341-379. Weng, L., Flammini, A., Vespignani, A., & Menczer, F. (2012). Competition among memes in a world with limited attention. Scientific Reports, 2(335). West, S. A., Griffin, A. S., & Gardner, A. (2008). Social semantics: how useful has group selection been? Journal of Evolutionary Biology, 21(1), 374-385. Whetsell, T. A., & Shields, P. M. (2013). The Dynamics of Positivism in the Study of Public Administration: A Brief Intellectual History and Reappraisal. Administration & Society. doi:10.1177/0095399713490157Whittaker, J., Courtial, J.-P., & Law, J. (1989). Creativity and Conformity in Science: Titles, Keywords and Co-Word Analysis. Social Studies of Science, 19(3), 473-496. Retrieved from http://www.jstor.org/stable/285083Wiley, J. A., & Martin, J. L. (1999). Algebraic Representations of Beliefs and Attitudes: Partial Order Models for Item Responses. Sociological Methodology, 29(1), 113-146. doi:10.1111/0081-1750.00062Wilkins, J. S. (2001). The Appearance of Lamarckism in the Evolution of Culture. In J. Laurent & J. Nightingale (Eds.), Darwinism and Evolutionary Economics (pp. 160-183): Edward Elgar Pub.Williams, C. K., Ives, A. R., & Applegate, R. D. (2003). Population Dynamics across Geographical Ranges: Time-Series Analyses of Three Small Game Species. Ecology, 84(10), 2654-2667. Retrieved from http://www.jstor.org/stable/3450110Woiwod, I. P., & Hanski, I. (1992). Patterns of Density Dependence in Moths and Aphids. Journal of Animal Ecology, 61(3), 619-629. doi:10.2307/5617Wu, Y.-C., Yang, L.-W., Shen, J.-Y., Chen, L.-Y., & Wu, S.-T. (2008). Tornado in Multilingual Opinion Analysis: A Transductive Learning Approach for Chinese Sentimental Polarity Recognition. Paper presented at the Proceedings of NTCIR-7 Workshop Meeting, Tokyo, Japan.Wu, Z., & Tseng, G. (1993). Chinese text segmentation for text retrieval: Achievements and problems. Journal of the American Society for Information Science, 44(9), 532-542. doi:10.1002/(SICI)1097-4571(199310)44:9<532::AID-ASI3>3.0.CO;2-MYang, Q., & Wu, X. (2006). 10 Challenging Problems in Data Mining Research. International Journal of Information Technology & Decision Making, 5(4), 597-604. Yoon, S. (2008). Using memes and memetic processes to explain social and conceptual influences on student understanding about complex socio-scientific issues. Journal of Research in Science Teaching, 45(8), 900-921. doi:10.1002/tea.20256Yu, B., Kaufmann, S., & Diermeier, D. (2008). Exploring the characteristics of opinion expressions for political opinion classification. Paper presented at the Proceedings of the 2008 international conference on Digital government research, Montreal, Canada. Zalmanovitch, Y. (2014). Don`t reinvent the wheel: the search for an identity for public administration. International Review of Administrative Sciences. doi:10.1177/0020852314533456Zelazny, R. (1967). Lord of Light (First Eos trade paperback ed.). United States of America: Doubleday & Company.Zikopoulos, P. C., deRoos, D., Parasuraman, K., Deutsch, T., Corrigan, D., & Giles, J. (2013). Harness the Power of Big Data: The IBM Big Data Platform R. B. Melnyk (Ed.) Zikopoulos, P. C., Eaton, C., DeRoos, D., Deutsch, T., & Lapis, G. (2012). Understanding Big Data: Analytics for Enterprise Class Hadoop and Streaming Data S. Sit (Ed.) zh_TW
