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| Title | 基於讀者回饋探勘有助於新聞社群經營之新聞資訊 Mining useful news information based on user feedback for building news community |
| Creator | 邱偉嘉 Chiu, Wei Chia |
| Contributor | 陳志銘<br>劉昭麟 Chen, Chih Ming<br>Liu, Chao Lin 邱偉嘉 Chiu, Wei Chia |
| Key Words | 協同式推薦系統 集體智慧 社會網路 新聞社群經營 模糊推論 |
| Date | 2009 |
| Date Issued | 9-Apr-2010 13:23:51 (UTC+8) |
| Summary | 近年來，由於網際網路的興起，網際網路已成為新聞媒體重要的傳播管道之一，許多新聞網站如雨後春筍般的成立，而讀者也樂於使用這類更加便利、高互動性的新聞網站。但是媒體使用網路作為傳播管道，同時也面臨在傳統傳播模式所未遭遇的新挑戰，網路新聞媒體被迫需要創造獨特的內容吸引使用者，也需發展具黏性的社群經營服務，才能與其他具有類似社群互動機制的Web 2.0網站一較長短，留住廣大的使用者群。 本研究嘗試利用新聞為日常生活人們獲得資訊不可或缺管道的獨特優勢，提出一套有效利用新聞使用社群集體智慧(Collective Intelligence）機制，能夠自動化依據使用者顯隱性回饋，針對每篇新聞分析出分歧度、熱門度、話題性三個社群資訊，並以上述三個社群資訊挑選出合適的焦點新聞，以此促進新聞社群使用者對於焦點新聞的討論與互動，進而提昇新聞傳播的效益與新聞社群的凝聚力。實驗結果證實，本研究所提出的機制確實能夠探勘出滿足大多數使用者關注焦點新聞資訊的需求，並且對於輔助記者掌握讀者對於新聞資訊需求及促進新聞社群經營方面都有很大的助益。 In recent years, due to the rise of the information and communication technologies, the internet has become one of most important communication channel for Journalism. A long with drastically flourished on-line Journalism, models of readers’ information reception changed while they are enjoyed more convenient and interactive websites providing instant information. At the same time, while mass media utilize internet as communication channel, it has also brought unprecedented challenge to traditional communication. On-line Journalism has not only need to create unique content (information) to attract readers; but it also need to develop a more engaging community management services to interact with other communities with similar mechanisms of Web 2.0 sites to retain user’s attention. This study attempts to exam the proposed on-line journalism system for University Press community, which could automatically analyze readers’ community dataset of University newspaper; including opinion deviation indicators, popularity indicator, and topicality indicator of each news (information). This system selects targeted news (information) according to above indicators to promote discussion and interactivity within readers’ community in hope to promote efficiency of news (information) communication and engagement within readers’ community. Experiment results reveal this proposed mechanism could satisfy most readers’ need for headline news; as well as assist Journalists’ understanding on their readers’ need while promoting on-line journalism social networking management. |
| 參考文獻 | [1] R. P. Adler, and A. J. Christopher. Internet Community Primer Overview and Business Opportunities. 1998. Retrieved November 24, 2009, from http://www.digitalplaces.biz/pages/printable_html.html. [2] C. Avery, and R. Zeckhauser, Recommender Systems for Evaluating Computer Messages, Communications of the ACM, Vol. 40, No. 3, 88-89, 1997. [3] B. Axford, and R. Huggins, New Media and Politics, Sage, 2001. [4] M. Balabanović, and Y. Shoham, Fab: Content-Based, Collaborative Recommendation, Communications of the ACM, Vol. 40, No. 3, 66-72, 1997. [5] A. Bruns, Blogs, Wikipedia, Second Life, and Beyond: From Production to Produsage, Peter Lang, New York, 2008. [6] M. Claypool, D. Brown, P. Le, and M. Waseda, Inferring User Interest, IEEE Internet Computing, 32-39, 2001. [7] T. Davenport, and J. Beck, The Attention Economy: Understanding the New Currency of Business, Harvard Business School Press, 2001. [8] D. Goldberg, D. Nichols, B. Oki, and D. Terry, Using Collaborative Filtering to Weave an Information Tapestry, Communications of the ACM, Vol. 35, No. 12, 61-70, 1992. [9] M. Goldhaber, The Attention Economy and the Net, First Monday, Vol. 2, No. 4, 1997. Retrieved November 24, 2009, from http://firstmonday.org/htbin/cgiwrap/bin/ojs/index.php/fm/article/viewArticle/519/440. [10] J. Grudin, Groupware and Social Dynamics: Eight Challenges for Developers, Communications of the ACM, Vol. 37, No. 1, 92-105, 1994. [11] J. Hagel III, and A. Armstrong, Net Gain: Expanding Markets through Virtual Communities, Harvard Business School Press, Boston, MA, 1997. [12] K. Hill, and J. Hughes, Cyberpolitics: Citizen Activism in the Age of the Internet, Rowman & Littlefield Publishers, Inc., 1998. [13] W. Hill, L. Stead, M. Rosenstein, and G. Furnas, Recommending and Evaluating Choices in a Virtual Community of Use, Proceedings of the SIGCHI Conference on Human Factors in Computing Systems. Vol. 3, No. 6, 20-21, 1995. [14] M. Igbaria, C. Shayo, and L. Olfman, On Becoming Virtual: The Driving Forces and Arrangements, Proceedings of the 1999 ACM SIGCPR Conference on Computer Personnel Research, 27-41, 1999. [15] I. Janis, Groupthink: Psychological Studies of Policy Decisions and Fiascoes, Houghton Mifflin, Boston, 1982. [16] I. Janis, Victims of Groupthink, Houghton Mifflin, Boston, 1972. [17] I. Janis, and L. Mann, Decision Making: A Psychological Analysis of Conflict, Choice, and Commitment, Free Press, New York, 1977. [18] T. Joachims, L. Granka, B. Pan, H. Hembrooke, F. Radlinski, and G. Gay, Evaluating the Accuracy of Implicit Feedback from Clicks and Query Reformulations in Web Search, ACM Transactions on Information Systems, Vol. 25, No. 2, 7, 2007. [19] S. Johnson, Internet Changes Everything: Revolutionizing Public Participation and Access to Government Information through the Internet, Administrative Law Review, Vol. 50, 277-337, 1998. [20] J. Konstan, B. Miller, D. Maltz, J. Herlocker, L. Gordon, and J. Riedl, GroupLens: Applying Collaborative Filtering to Usenet News, Communications of the ACM, Vol. 40, No. 3, 77-87, 1997. [21] C. Lee, Fuzzy Logic in Control Systems: Fuzzy Logic Controller--part I, IEEE Transactions on Systems, Man, and Cybernetics, Vol. 20, No. 2, 404-418, 1990. [22] F. S. L. Lee, D. Vogel, and M. Limayem, Virtual Community Informatics: What We Know and What We Need to Know, Proceedings of the 35th Hawaii International Conference on System Sciences, 2863-2872, 2002. [23] B. McEvily, V. Perrone, and A. Zaheer, Trust as an Organizing Principle, Organization Science, Vol. 14, No. 1, 91-103, 2003. [24] M. Morita, and Y. Shinoda, Information Filtering Based on User Behavior Analysis and Best Match Text Retrieval, Proceedings of the 17th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, 272-281, 1994. [25] M. Morris, and C. Ogan, The Internet as Mass Medium, Journal of Computer-Mediated Communication, Vol. 46, No. 1, 39-50, 1996. [26] D. M. Nichols, Implicit Rating and Filtering, Proceedings of the Fifth DELOS Workshop on Filteringan d Collaborative Filtering, 31-36, 1997. [27] D. Oard, and G. Marchionini, A Conceptual Framework for Text Filtering, Technical Report CS-TR-3643, 1996. [28] J. Palme, Choices in the Implementation of Rating, Oldenbourg, Vienna, Austria, 1997. [29] J. Pavlik, and P. Sagan, The Future of Online Journalism: Bonanza or Black Hole?, Columbia Journalism Review, Vol. 36, No. 2, 30-38, 1997. [30] P. Resnick, N. Iacovou, M. Suchak, P. Bergstrom, and J. Riedl, GroupLens: An Open Architecture for Collaborative Filtering of Netnews, Proceedings of the 1994 ACM Conference on Computer Supported Cooperative Work, 175-186, 1994. [31] H. Rheingold, The Virtual Community: Homesteading on the Electronic Frontier, MIT press, 2000. [32] C. Shannon, A Mathematical Theory of Communication, ACM SIGMOBILE Mobile Computing and Communications Review, Vol. 5, No. 1, 3-55, 2001. [33] U. Shardanand, and P. Maes, Social Information Filtering: Algorithms for Automating "Word of Mouth", Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, 210-217, 1995. [34] D. Shenk, Data Smog: Surviving the Information Glut, HarperOne, San Francisco, 1998. [35] C. L. Sia, B. C. Y. Tan, and K. K. Wei, Group Polarization and Computer-Mediated Communication: Effects of Communication Cues, Social Presence, and Anonymity, Information Systems Research, Vol. 13, No. 1, 70-90, 2002. [36] M. Spiliopoulou, and L. Faulstich, Wum: A Web Utilization Miner, Proceedings of the International Workshop on the Web and Databases, 109-115, 1999. [37] C. Sunstein, Democracy and Filtering, Communications of the ACM, Vol. 47, No. 12, 57-59, 2004. [38] C. Sunstein, Republic. com 2.0, Princeton University Press, 2007. [39] J. Surowiecki, and M. Silverman, The Wisdom of Crowds, American Journal of Physics, Vol. 75, No. 2, 190-192, 2007. [40] A. Swartz. Raw Thought: Who Writes Wikipedia. 2006. Retrieved November 24, 2009, from http://www.aaronsw.com/weblog/whowriteswikipedia. [41] A. M. A. Wasfi, Collecting User Access Patterns for Building User Profiles and Collaborative Filtering, Proceedings of the 4th International Conference on Intelligent User Interfaces, 1999. [42] G. Webb, M. Pazzani, and D. Billsus, Machine Learning for User Modeling, User Modeling and User-Adapted Interaction, Vol. 11, No. 1, 19-29, 2001. [43] R. White, I. Ruthven, and J. M. Jose, The Use of Implicit Evidence for Relevance Feedback in Web Retrieval, Proceedings of the 24th BCS-IRSG European Colloquium on IR Research: Advances in Information Retrieval, 93-109, 2002. [44] L. Zadeh, Fuzzy Sets, Information and Control, Vol. 8, No. 3, 338-353, 1965. [45] 施盈廷, 線上新聞媒體的角色定位: 從內容提供者到公共辯論的倡導者, 中華傳播學刊, No. 12, 53-87, 2007. |
| Description | 碩士 國立政治大學 資訊科學學系 96753012 98 |
| 資料來源 | http://thesis.lib.nccu.edu.tw/record/#G0096753012 |
| Type | thesis |
| dc.contributor.advisor | 陳志銘<br>劉昭麟 | zh_TW |
| dc.contributor.advisor | Chen, Chih Ming<br>Liu, Chao Lin | en_US |
| dc.contributor.author (Authors) | 邱偉嘉 | zh_TW |
| dc.contributor.author (Authors) | Chiu, Wei Chia | en_US |
| dc.creator (作者) | 邱偉嘉 | zh_TW |
| dc.creator (作者) | Chiu, Wei Chia | en_US |
| dc.date (日期) | 2009 | en_US |
| dc.date.accessioned | 9-Apr-2010 13:23:51 (UTC+8) | - |
| dc.date.available | 9-Apr-2010 13:23:51 (UTC+8) | - |
| dc.date.issued (上傳時間) | 9-Apr-2010 13:23:51 (UTC+8) | - |
| dc.identifier (Other Identifiers) | G0096753012 | en_US |
| dc.identifier.uri (URI) | http://nccur.lib.nccu.edu.tw/handle/140.119/38542 | - |
| 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) | 96753012 | zh_TW |
| dc.description (描述) | 98 | zh_TW |
| dc.description.abstract (摘要) | 近年來，由於網際網路的興起，網際網路已成為新聞媒體重要的傳播管道之一，許多新聞網站如雨後春筍般的成立，而讀者也樂於使用這類更加便利、高互動性的新聞網站。但是媒體使用網路作為傳播管道，同時也面臨在傳統傳播模式所未遭遇的新挑戰，網路新聞媒體被迫需要創造獨特的內容吸引使用者，也需發展具黏性的社群經營服務，才能與其他具有類似社群互動機制的Web 2.0網站一較長短，留住廣大的使用者群。 本研究嘗試利用新聞為日常生活人們獲得資訊不可或缺管道的獨特優勢，提出一套有效利用新聞使用社群集體智慧(Collective Intelligence）機制，能夠自動化依據使用者顯隱性回饋，針對每篇新聞分析出分歧度、熱門度、話題性三個社群資訊，並以上述三個社群資訊挑選出合適的焦點新聞，以此促進新聞社群使用者對於焦點新聞的討論與互動，進而提昇新聞傳播的效益與新聞社群的凝聚力。實驗結果證實，本研究所提出的機制確實能夠探勘出滿足大多數使用者關注焦點新聞資訊的需求，並且對於輔助記者掌握讀者對於新聞資訊需求及促進新聞社群經營方面都有很大的助益。 | zh_TW |
| dc.description.abstract (摘要) | In recent years, due to the rise of the information and communication technologies, the internet has become one of most important communication channel for Journalism. A long with drastically flourished on-line Journalism, models of readers’ information reception changed while they are enjoyed more convenient and interactive websites providing instant information. At the same time, while mass media utilize internet as communication channel, it has also brought unprecedented challenge to traditional communication. On-line Journalism has not only need to create unique content (information) to attract readers; but it also need to develop a more engaging community management services to interact with other communities with similar mechanisms of Web 2.0 sites to retain user’s attention. This study attempts to exam the proposed on-line journalism system for University Press community, which could automatically analyze readers’ community dataset of University newspaper; including opinion deviation indicators, popularity indicator, and topicality indicator of each news (information). This system selects targeted news (information) according to above indicators to promote discussion and interactivity within readers’ community in hope to promote efficiency of news (information) communication and engagement within readers’ community. Experiment results reveal this proposed mechanism could satisfy most readers’ need for headline news; as well as assist Journalists’ understanding on their readers’ need while promoting on-line journalism social networking management. | en_US |
| dc.description.tableofcontents | 第一章 緒論 1 1.1 研究背景與動機 1 1.2 研究目的 3 1.3 問題陳述 4 1.4 章節架構 4 第二章 文獻探討 6 2.1 線上新聞網站的發展與未來 6 2.2 團體討論與決策行為 10 2.3 使用者回饋之分類 15 2.4 協同式推薦系統介紹 18 2.5 隱性回饋 20 2.6 小結 22 第三章 研究方法 25 3.1 新聞社群互動模式 25 3.2 系統架構 27 3.2.1 系統運作流程 29 3.3 推論代理人 30 3.3.1 分歧度計算 31 3.3.2 熱門度與話題性 31 3.3.3 焦點分數 32 3.3.4 模糊邏輯推論 33 3.3.5 決定模糊歸屬函數 34 3.3.6 建立模糊規則 36 3.3.7 解模糊化 38 3.4 系統實作 38 第四章 實驗設計 42 4.1 實驗對象 42 4.2 社群分析 43 4.3 網站使用狀況探勘 44 4.4 問卷調查及分析 46 4.5 研究限制 47 第五章 研究結果分析與討論 48 5.1 新聞基本資料分析 48 5.2 讀者回饋資訊分析 49 5.3 網站使用分析 56 5.4 社會網路分析 59 5.5 問卷分析 65 5.6 新聞案例分析 69 5.7 大學報實習記者訪談 71 第六章 結論與未來展望 73 6.1 結論 73 6.2 未來展望 75 參考文獻 77 附錄一 使用者問卷調查表 81 附錄二 使用者問卷之對於本系統的意見調查表 83 附錄三 新聞《人肉搜索揪關鍵人物》 86 附錄四 大學報實習記者與編輯訪談實錄 88 附錄五 大學報總編輯及副總編輯訪談實錄 93 | zh_TW |
| dc.format.extent | 2560843 bytes | - |
| dc.format.mimetype | application/pdf | - |
| dc.language.iso | en_US | - |
| dc.source.uri (資料來源) | http://thesis.lib.nccu.edu.tw/record/#G0096753012 | en_US |
| dc.subject (關鍵詞) | 協同式推薦系統 | zh_TW |
| dc.subject (關鍵詞) | 集體智慧 | zh_TW |
| dc.subject (關鍵詞) | 社會網路 | zh_TW |
| dc.subject (關鍵詞) | 新聞社群經營 | zh_TW |
| dc.subject (關鍵詞) | 模糊推論 | zh_TW |
| dc.title (題名) | 基於讀者回饋探勘有助於新聞社群經營之新聞資訊 | zh_TW |
| dc.title (題名) | Mining useful news information based on user feedback for building news community | en_US |
| dc.type (資料類型) | thesis | en |
| dc.relation.reference (參考文獻) | [1] R. P. Adler, and A. J. Christopher. Internet Community Primer Overview and Business Opportunities. 1998. Retrieved November 24, 2009, from http://www.digitalplaces.biz/pages/printable_html.html. | zh_TW |
| dc.relation.reference (參考文獻) | [2] C. Avery, and R. Zeckhauser, Recommender Systems for Evaluating Computer Messages, Communications of the ACM, Vol. 40, No. 3, 88-89, 1997. | zh_TW |
| dc.relation.reference (參考文獻) | [3] B. Axford, and R. Huggins, New Media and Politics, Sage, 2001. | zh_TW |
| dc.relation.reference (參考文獻) | [4] M. Balabanović, and Y. Shoham, Fab: Content-Based, Collaborative Recommendation, Communications of the ACM, Vol. 40, No. 3, 66-72, 1997. | zh_TW |
| dc.relation.reference (參考文獻) | [5] A. Bruns, Blogs, Wikipedia, Second Life, and Beyond: From Production to Produsage, Peter Lang, New York, 2008. | zh_TW |
| dc.relation.reference (參考文獻) | [6] M. Claypool, D. Brown, P. Le, and M. Waseda, Inferring User Interest, IEEE Internet Computing, 32-39, 2001. | zh_TW |
| dc.relation.reference (參考文獻) | [7] T. Davenport, and J. Beck, The Attention Economy: Understanding the New Currency of Business, Harvard Business School Press, 2001. | zh_TW |
| dc.relation.reference (參考文獻) | [8] D. Goldberg, D. Nichols, B. Oki, and D. Terry, Using Collaborative Filtering to Weave an Information Tapestry, Communications of the ACM, Vol. 35, No. 12, 61-70, 1992. | zh_TW |
| dc.relation.reference (參考文獻) | [9] M. Goldhaber, The Attention Economy and the Net, First Monday, Vol. 2, No. 4, 1997. Retrieved November 24, 2009, from http://firstmonday.org/htbin/cgiwrap/bin/ojs/index.php/fm/article/viewArticle/519/440. | zh_TW |
| dc.relation.reference (參考文獻) | [10] J. Grudin, Groupware and Social Dynamics: Eight Challenges for Developers, Communications of the ACM, Vol. 37, No. 1, 92-105, 1994. | zh_TW |
| dc.relation.reference (參考文獻) | [11] J. Hagel III, and A. Armstrong, Net Gain: Expanding Markets through Virtual Communities, Harvard Business School Press, Boston, MA, 1997. | zh_TW |
| dc.relation.reference (參考文獻) | [12] K. Hill, and J. Hughes, Cyberpolitics: Citizen Activism in the Age of the Internet, Rowman & Littlefield Publishers, Inc., 1998. | zh_TW |
| dc.relation.reference (參考文獻) | [13] W. Hill, L. Stead, M. Rosenstein, and G. Furnas, Recommending and Evaluating Choices in a Virtual Community of Use, Proceedings of the SIGCHI Conference on Human Factors in Computing Systems. Vol. 3, No. 6, 20-21, 1995. | zh_TW |
| dc.relation.reference (參考文獻) | [14] M. Igbaria, C. Shayo, and L. Olfman, On Becoming Virtual: The Driving Forces and Arrangements, Proceedings of the 1999 ACM SIGCPR Conference on Computer Personnel Research, 27-41, 1999. | zh_TW |
| dc.relation.reference (參考文獻) | [15] I. Janis, Groupthink: Psychological Studies of Policy Decisions and Fiascoes, Houghton Mifflin, Boston, 1982. | zh_TW |
| dc.relation.reference (參考文獻) | [16] I. Janis, Victims of Groupthink, Houghton Mifflin, Boston, 1972. | zh_TW |
| dc.relation.reference (參考文獻) | [17] I. Janis, and L. Mann, Decision Making: A Psychological Analysis of Conflict, Choice, and Commitment, Free Press, New York, 1977. | zh_TW |
| dc.relation.reference (參考文獻) | [18] T. Joachims, L. Granka, B. Pan, H. Hembrooke, F. Radlinski, and G. Gay, Evaluating the Accuracy of Implicit Feedback from Clicks and Query Reformulations in Web Search, ACM Transactions on Information Systems, Vol. 25, No. 2, 7, 2007. | zh_TW |
| dc.relation.reference (參考文獻) | [19] S. Johnson, Internet Changes Everything: Revolutionizing Public Participation and Access to Government Information through the Internet, Administrative Law Review, Vol. 50, 277-337, 1998. | zh_TW |
| dc.relation.reference (參考文獻) | [20] J. Konstan, B. Miller, D. Maltz, J. Herlocker, L. Gordon, and J. Riedl, GroupLens: Applying Collaborative Filtering to Usenet News, Communications of the ACM, Vol. 40, No. 3, 77-87, 1997. | zh_TW |
| dc.relation.reference (參考文獻) | [21] C. Lee, Fuzzy Logic in Control Systems: Fuzzy Logic Controller--part I, IEEE Transactions on Systems, Man, and Cybernetics, Vol. 20, No. 2, 404-418, 1990. | zh_TW |
| dc.relation.reference (參考文獻) | [22] F. S. L. Lee, D. Vogel, and M. Limayem, Virtual Community Informatics: What We Know and What We Need to Know, Proceedings of the 35th Hawaii International Conference on System Sciences, 2863-2872, 2002. | zh_TW |
| dc.relation.reference (參考文獻) | [23] B. McEvily, V. Perrone, and A. Zaheer, Trust as an Organizing Principle, Organization Science, Vol. 14, No. 1, 91-103, 2003. | zh_TW |
| dc.relation.reference (參考文獻) | [24] M. Morita, and Y. Shinoda, Information Filtering Based on User Behavior Analysis and Best Match Text Retrieval, Proceedings of the 17th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, 272-281, 1994. | zh_TW |
| dc.relation.reference (參考文獻) | [25] M. Morris, and C. Ogan, The Internet as Mass Medium, Journal of Computer-Mediated Communication, Vol. 46, No. 1, 39-50, 1996. | zh_TW |
| dc.relation.reference (參考文獻) | [26] D. M. Nichols, Implicit Rating and Filtering, Proceedings of the Fifth DELOS Workshop on Filteringan d Collaborative Filtering, 31-36, 1997. | zh_TW |
| dc.relation.reference (參考文獻) | [27] D. Oard, and G. Marchionini, A Conceptual Framework for Text Filtering, Technical Report CS-TR-3643, 1996. | zh_TW |
| dc.relation.reference (參考文獻) | [28] J. Palme, Choices in the Implementation of Rating, Oldenbourg, Vienna, Austria, 1997. | zh_TW |
| dc.relation.reference (參考文獻) | [29] J. Pavlik, and P. Sagan, The Future of Online Journalism: Bonanza or Black Hole?, Columbia Journalism Review, Vol. 36, No. 2, 30-38, 1997. | zh_TW |
| dc.relation.reference (參考文獻) | [30] P. Resnick, N. Iacovou, M. Suchak, P. Bergstrom, and J. Riedl, GroupLens: An Open Architecture for Collaborative Filtering of Netnews, Proceedings of the 1994 ACM Conference on Computer Supported Cooperative Work, 175-186, 1994. | zh_TW |
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