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題名 政治人物之社交網絡建置與分析
Constructing and Analyzing Social Networks of Politicians
作者 黃羿綺
Huang, Yi Chi
貢獻者 陳良弼
Chen, L. P.
黃羿綺
Huang, Yi Chi
關鍵詞 社會網絡
日期 2014
上傳時間 2-Mar-2015 10:13:22 (UTC+8)
摘要 由於時代的變遷，資訊量以倍數成長，隨著科技的進步如何有效率的利用資訊技術處理這些大量資料是這幾年被廣泛研究的議題之一。在大量且雜亂的資料中，如何尋找人與人之間的關係並且推測出其中所隱含的資訊，可以透過社會網絡分析對個人或是群體進行觀察。早期的社會網絡分析較著重在靜態網絡分析，亦即不考慮時間因素的情況下所建置的網絡，但現實中人與人之間的關係會隨著時間的改變而有所不同。
     本研究希望建置一個政治人物的社交網絡，尋找此社交網絡中隱含的資訊。資料來源以中央選舉委員會提供之選舉公報為主，將每位候選人視為網絡之節點並蒐集候選人的相關資料。一個網絡的建立需要關係作為節點間連結，因此需要將關係作一個明確的定義。最後，根據不同關係建立的網絡，使用社會網絡分析挖掘出有用的資訊。另外可藉由蒐集的資料提供與政治人物相關的查詢。
In recent years, the explosion of data is alarming. How to efficiently process
     
     this data to get useful information from it becomes an important issue. At the
     
     same time, theory for analyzing large social networks has been developed. It
     
     allows us to explore some special individuals, for example, the maximum
     
     influential individual in a social network.
     
     In this thesis, we define multiple relationships of Taiwan politicians to
     
     construct various social networks. In order to get special individuals in each
     
     social network, we use three of the popular indicators to calculate the centrality
     
     of the networks. We also implement a system that can show the social networks
     
     as well as the query and analysis results from these networks.
參考文獻 [1] A. Abelló, & C. C. Martín, “The Data Warehouse: An Object-Oriented Temporal Database,” Proceedings of Jornadas de Ingeniería del Software y Bases de Datos(JISBD’03), pp. 675-684, 2003.
     [2] G. Ozsoyoglu, & R.T. Snodgrass, “Temporal and Real-Time Databases: A Survey,” IEEE Transactions on Knowledge and Data Engineering, 7(4), pp. 513-532, 1995.
     [3] J. A. Barnes, “Class and Committees in a Norwegian Island Parish,” Human Relations, 7(1), pp. 39-58, 1954.
     [4] J. Scott, “Social Network Analysis: A Handbook,” SAGE Publishers, 2000.
     [5] K. Faust, “Centrality in Affiliation Networks,” Social Networks, 19(2), pp. 157-191, 1997.
     [6] L. C. Freeman, “Centrality in Social Networks Conceptual Clarification,” Social Networks, 1(3), pp. 215-239, 1979.
     [7] M. Al-Kateb, E. Mansour, & M. E. El-Sharkawi, “CME: A Temporal Relational Model for Efficient Coalescing,” Proceedings of International Symposium on Temporal Representation and Reasoning, pp. 83-90, 2005.
     [8] M. H. Bohlen, R. T. Snodgrass, & M. D. Soo, “Coalescing in Temporal Database,” Proceedings of International Conference on Very Large Data Bases (VLDB’96), pp. 180-191, 1996.
     [9] N. Mahmood, A. Burney, & K. Ahsan, “A Logical Temporal Relational Data Model,” International Journal of Computer Science Issues, 7(1), pp. 1-9, 2010.
     [10] P. J. Carrington, J. Scott, & S. Wasserman, “Models and Methods in Social Network Analysis,” Cambridge University Press, 2005.
     [11] R. A. Hanneman, & M. Riddle, “Introduction to Social Network Methods,” Published in digital form at http://faculty.ucr.edu/~hanneman/, 2005.
     [12] R. T. Snodgrass, M. Jim, “Developing Time-Oriented Database Applications in SQL,” Morgan Kaufmann Publishers, 2000.
     [13] X. Zhou, F. Wang, & C. Zaniolo, “Efficient Temporal Coalescing Query Support in Relational Database Systems,” Proceedings of International Conference on Database and Expert Systems Applications (DEXA’06), pp. 676-686, 2006.
描述 碩士
國立政治大學
資訊科學學系
101753009
103
資料來源 http://thesis.lib.nccu.edu.tw/record/#G0101753009
資料類型 thesis
dc.contributor.advisor 陳良弼zh_TW
dc.contributor.advisor Chen, L. P.en_US
dc.contributor.author (Authors) 黃羿綺zh_TW
dc.contributor.author (Authors) Huang, Yi Chien_US
dc.creator (作者) 黃羿綺zh_TW
dc.creator (作者) Huang, Yi Chien_US
dc.date (日期) 2014en_US
dc.date.accessioned 2-Mar-2015 10:13:22 (UTC+8)-
dc.date.available 2-Mar-2015 10:13:22 (UTC+8)-
dc.date.issued (上傳時間) 2-Mar-2015 10:13:22 (UTC+8)-
dc.identifier (Other Identifiers) G0101753009en_US
dc.identifier.uri (URI) http://nccur.lib.nccu.edu.tw/handle/140.119/73571-
dc.description (描述) 碩士zh_TW
dc.description (描述) 國立政治大學zh_TW
dc.description (描述) 資訊科學學系zh_TW
dc.description (描述) 101753009zh_TW
dc.description (描述) 103zh_TW
dc.description.abstract (摘要) 由於時代的變遷，資訊量以倍數成長，隨著科技的進步如何有效率的利用資訊技術處理這些大量資料是這幾年被廣泛研究的議題之一。在大量且雜亂的資料中，如何尋找人與人之間的關係並且推測出其中所隱含的資訊，可以透過社會網絡分析對個人或是群體進行觀察。早期的社會網絡分析較著重在靜態網絡分析，亦即不考慮時間因素的情況下所建置的網絡，但現實中人與人之間的關係會隨著時間的改變而有所不同。
     本研究希望建置一個政治人物的社交網絡，尋找此社交網絡中隱含的資訊。資料來源以中央選舉委員會提供之選舉公報為主，將每位候選人視為網絡之節點並蒐集候選人的相關資料。一個網絡的建立需要關係作為節點間連結，因此需要將關係作一個明確的定義。最後，根據不同關係建立的網絡，使用社會網絡分析挖掘出有用的資訊。另外可藉由蒐集的資料提供與政治人物相關的查詢。		zh_TW
dc.description.abstract (摘要) In recent years, the explosion of data is alarming. How to efficiently process
     
     this data to get useful information from it becomes an important issue. At the
     
     same time, theory for analyzing large social networks has been developed. It
     
     allows us to explore some special individuals, for example, the maximum
     
     influential individual in a social network.
     
     In this thesis, we define multiple relationships of Taiwan politicians to
     
     construct various social networks. In order to get special individuals in each
     
     social network, we use three of the popular indicators to calculate the centrality
     
     of the networks. We also implement a system that can show the social networks
     
     as well as the query and analysis results from these networks.		en_US
dc.description.tableofcontents 第一章 緒論 1
     第二章 文獻探討 3
     2.1社會網絡(Social Network) 3
     2.1.1 社會網絡組成要素 3
     2.1.2 社會網絡指標 4
     2.2時間資料庫(Temporal Database) 8
     2.3時間聚合(Temporal Coalescing) 9
     第三章 社交網絡之建置 11
     3.1 系統架構 11
     3.2 資料蒐集 12
     3.3 定義政治人物之社交關係 13
     3.3.1 資料儲存格式 13
     3.3.2 定義屬性 15
     3.3.3 定義關係 16
     3.3.4 定義時間 17
     3.3.5 定義階層 19
     第四章 社交網絡之分析與查詢 21
     4.1 親屬關係之分析 21
     4.2 非時間性關係之分析 23
     4.2.1 同校關係 23
     4.2.2 同機構關係 26
     4.3 時間性關係之分析 29
     4.3.1 同學關係、學長弟關係及校友關係 29
     4.3.2 同事關係及從屬關係 32
     4.3.3 師生關係 37
     4.4 查詢介面 39
     4.5 討論 42
     第五章 結論 43
     參考文獻 44		zh_TW
dc.source.uri (資料來源) http://thesis.lib.nccu.edu.tw/record/#G0101753009en_US
dc.subject (關鍵詞) 社會網絡zh_TW
dc.title (題名) 政治人物之社交網絡建置與分析zh_TW
dc.title (題名) Constructing and Analyzing Social Networks of Politiciansen_US
dc.type (資料類型) thesisen
dc.relation.reference (參考文獻) [1] A. Abelló, & C. C. Martín, “The Data Warehouse: An Object-Oriented Temporal Database,” Proceedings of Jornadas de Ingeniería del Software y Bases de Datos(JISBD’03), pp. 675-684, 2003.
     [2] G. Ozsoyoglu, & R.T. Snodgrass, “Temporal and Real-Time Databases: A Survey,” IEEE Transactions on Knowledge and Data Engineering, 7(4), pp. 513-532, 1995.
     [3] J. A. Barnes, “Class and Committees in a Norwegian Island Parish,” Human Relations, 7(1), pp. 39-58, 1954.
     [4] J. Scott, “Social Network Analysis: A Handbook,” SAGE Publishers, 2000.
     [5] K. Faust, “Centrality in Affiliation Networks,” Social Networks, 19(2), pp. 157-191, 1997.
     [6] L. C. Freeman, “Centrality in Social Networks Conceptual Clarification,” Social Networks, 1(3), pp. 215-239, 1979.
     [7] M. Al-Kateb, E. Mansour, & M. E. El-Sharkawi, “CME: A Temporal Relational Model for Efficient Coalescing,” Proceedings of International Symposium on Temporal Representation and Reasoning, pp. 83-90, 2005.
     [8] M. H. Bohlen, R. T. Snodgrass, & M. D. Soo, “Coalescing in Temporal Database,” Proceedings of International Conference on Very Large Data Bases (VLDB’96), pp. 180-191, 1996.
     [9] N. Mahmood, A. Burney, & K. Ahsan, “A Logical Temporal Relational Data Model,” International Journal of Computer Science Issues, 7(1), pp. 1-9, 2010.
     [10] P. J. Carrington, J. Scott, & S. Wasserman, “Models and Methods in Social Network Analysis,” Cambridge University Press, 2005.
     [11] R. A. Hanneman, & M. Riddle, “Introduction to Social Network Methods,” Published in digital form at http://faculty.ucr.edu/~hanneman/, 2005.
     [12] R. T. Snodgrass, M. Jim, “Developing Time-Oriented Database Applications in SQL,” Morgan Kaufmann Publishers, 2000.
     [13] X. Zhou, F. Wang, & C. Zaniolo, “Efficient Temporal Coalescing Query Support in Relational Database Systems,” Proceedings of International Conference on Database and Expert Systems Applications (DEXA’06), pp. 676-686, 2006.		zh_TW