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題名 自適應社群網路服務：以九校EMBA社群為例
Adaptive Social Network Services: The Practice of 9EMBA.COM
作者 鄭巧翊
貢獻者 郁方
鄭巧翊
關鍵詞 社群網路服務
虛擬社群
高階經理人管理碩士
Adaptive social network
Virtual community
Executive MBA
日期 2017
上傳時間 28-Aug-2017 14:16:09 (UTC+8)
摘要 社群網路服務在我們的生活中扮演著不可或缺的角色，而其型態也隨著人們的網路使用習慣而改變。我們推導出下一世代的社群網路服務將會圍繞著企業會組織所經營之特定用意的社群，並從自我品牌經營的策略出發，研究輔助虛擬社群成長的各項關鍵服務，經由分析與設計並提出社群廣場之框架。我們的社群廣場結合了內容、社群、交流以及經營自我品牌服務作為關鍵服務，並透過（隱性）標籤鏈結讓虛擬社群中的實體以及服務得以連結。為了評估本研究提出的方法，我們以台灣九所頂尖大學高階工商管理學生（EMBA）的社群為實作對象，開發了一個全新的社群平台9EMBA.COM。初步的調查中顯示，EMBA學生都非常滿意這個社群平台。
參考文獻 [1] D. M. Boyd and N. B. Ellison, “Social Network Sites: Definition, History, and Scholarship,” Journal of Computer-Mediated Communication, vol. 13, no. 1, pp. 210–230, Oct. 2007.
[2] O. Kwon and Y. Wen, “An empirical study of the factors affecting social network service use,” Computers in Human Behavior, vol. 26, no. 2, pp. 254–263, Mar. 2010.
[3] “MiGente.com — Where Latinos \\& Latinas Meet to Chat, Discuss, Engage.” [Online]. Available: http://www.migente.com/. [Accessed: 21-Feb-2017].
[4] “Featured Content on Myspace.” [Online]. Available: https://myspace.com/. [Accessed: 21-Feb-2017].
[5] “YouTube.” [Online]. Available: https://www.youtube.com/. [Accessed: 21-Feb-2017].
[6] “Instagram,” Instagram. [Online]. Available: https://instagram.com/. [Accessed: 21-Feb-2017].
[7] “Facebook.” [Online]. Available: https://www.facebook.com/. [Accessed: 21-Feb-2017].
[8] “Facebook.” [Online]. Available: https://www.friendster.com/. [Accessed: 21-Feb-2017].
[9] “Pinterest • The world’s catalog of ideas.” [Online]. Available: https://www.pinterest.com/. [Accessed: 21-Feb-2017].
[10] “Yahoo.” [Online]. Available: https://www.yahoo.com/. [Accessed: 21-Feb-2017].
[11] “LinkedIn: Log In or Sign Up.” [Online]. Available: https://www.linkedin.com/. [Accessed: 21-Feb-2017].
[12] “WeChat - Free messaging and calling app.” [Online]. Available: https://www.wechat.com/en/. [Accessed: 21-Feb-2017].
[13] “Twitter. It’s what’s happening.” [Online]. Available: https://twitter.com/?lang=en. [Accessed: 21-Feb-2017].
[14] “9EMBA-HOME.” [Online]. Available: http://9emba.com/articles. [Accessed: 22-Feb-2017].
[15] “Drupal - Open Source CMS | Drupal.org.” [Online]. Available: https://www.drupal.org/. [Accessed: 21-Feb-2017].
[16] “Blog Tool, Publishing Platform, and CMS — WordPress.” [Online]. Available: https://wordpress.org/. [Accessed: 21-Feb-2017].
[17] “The 16 Best Facebook Pages You’ve Ever Seen.” [Online]. Available: https://blog.hubspot.com/blog/tabid/6307/bid/28441/the-15-best-facebook-pages-you-ve-ever-seen.aspx. [Accessed: 14-Feb-2017].
[18] “Starbucks.” [Online]. Available: https://www.facebook.com/Starbucks/. [Accessed: 18-Feb-2017].
[19] “ME MEDIA: Points of View Reference Center Home.” [Online]. Available: http://web.b.ebscohost.com/pov/detail/detail?sid=209cced7-adcf-421d-ba43-f669ae64d40f [Accessed: 14-Feb-2017].
[20] Li, Honglei. "Virtual community studies: A literature review, synthesis and research agenda." AMCIS 2004 Proceedings (2004): 324.
[21] J. Hagel, “Net Gain: Expanding Markets Through Virtual Communities,” Journal of Interactive Marketing (John Wiley \\& Sons), vol. 13, no. 1, pp. 55–65, Winter 1999.
[22] J. Bacon, The Art of Community: Building the New Age of Participation. O’Reilly Media, Inc., 2012.
[23] J. H. Kietzmann, K. Hermkens, I. P. McCarthy, and B. S. Silvestre, “Social media? Get serious! Understanding the functional building blocks of social media,” Business Horizons, vol. 54, no. 3, pp. 241–251, May 2011.
[24] A. Rae, B. Sigurbjörnsson, and R. van Zwol, “Improving Tag Recommendation Using Social Networks,” in Adaptivity, Personalization and Fusion of Heterogeneous Information, Paris, France, France, 2010, pp. 92–99.
[25] “Web,” Google Developers. [Online]. Available: https://developers.google.com/web/progressive-web-apps/. [Accessed: 15-Feb-2017].
[26] M. P. Papazoglou, V. Andrikopoulos, and S. Benbernou, “Managing Evolving Services,” IEEE Software, vol. 28, no. 3, pp. 49–55, May 2011.
[27] S. A. Barab, “An Introduction to the Special Issue: Designing for Virtual Communities in the Service of Learning,” Information Society, vol. 19, no. 3, p. 197, Aug. 2003.
[28] S. Thomaidou and M. Vazirgiannis, “Multiword Keyword Recommendation System for Online Advertising,” in 2011 International Conference on Advances in Social Networks Analysis and Mining, 2011, pp. 423–427.
[29] P. Kazienko, K. Musial, and T. Kajdanowicz, “Multidimensional Social Network in the Social Recommender System,” IEEE Transactions on Systems, Man, and Cybernetics - Part A: Systems and Humans, vol. 41, no. 4, pp. 746–759, Jul. 2011.
[30] C. Marlow, M. Naaman, D. Boyd, and M. Davis, “HT06, Tagging Paper, Taxonomy, Flickr, Academic Article, to Read,” in Proceedings of the Seventeenth Conference on Hypertext and Hypermedia, New York, NY, USA, 2006, pp. 31–40.
[31] S. Ahern, M. Naaman, R. Nair, and J. H.-I. Yang, “World Explorer: Visualizing Aggregate Data from Unstructured Text in Geo-referenced Collections,” in Proceedings of the 7th ACM/IEEE-CS Joint Conference on Digital Libraries, New York, NY, USA, 2007, pp. 1–10.
[32] D. Kempe, J. Kleinberg, and É. Tardos, “Maximizing the Spread of Influence Through a Social Network,” in Proceedings of the Ninth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, New York, NY, USA, 2003, pp. 137–146.
[33] A. S. Das, M. Datar, A. Garg, and S. Rajaram, “Google News Personalization: Scalable Online Collaborative Filtering,” in Proceedings of the 16th International Conference on World Wide Web, New York, NY, USA, 2007, pp. 271–280.
[34] B. Sarwar, G. Karypis, J. Konstan, and J. Riedl, “Item-based Collaborative Filtering Recommendation Algorithms,” in Proceedings of the 10th International Conference on World Wide Web, New York, NY, USA, 2001, pp. 285–295.
[35] M. Deshpande and G. Karypis, “Item-based top-N Recommendation Algorithms,” ACM Trans. Inf. Syst., vol. 22, no. 1, pp. 143–177, Jan. 2004.
[36] A. Salah, N. Rogovschi, and M. Nadif, “A dynamic collaborative filtering system via a weighted clustering approach,” Neurocomputing, vol. 175, pp. 206–215, Jan. 2016.
[37] K. Lang, “NewsWeeder: Learning to Filter Netnews,” in in Proceedings of the 12th International Machine Learning Conference (ML95, 1995.
[38] B. Krulwich and C. Burkey, “The InfoFinder agent: learning user interests through heuristic phrase extraction,” IEEE Expert, vol. 12, no. 5, pp. 22–27, Sep. 1997
[39] W. Hill, L. Stead, M. Rosenstein, and G. Furnas, “Recommending and Evaluating Choices in a Virtual Community of Use,” in Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, New York, NY, USA, 1995, pp. 194–201.
[40] U. Shardanand and P. Maes, “Social Information Filtering: Algorithms for Automating ‘Word of Mouth,’” in Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, New York, NY, USA, 1995, pp. 210–217.
[41] H. Ma, I. King, and M. R. Lyu, “Effective Missing Data Prediction for Collaborative Filtering,” in Proceedings of the 30th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, New York, NY, USA, 2007, pp. 39–46.
[42] P. Melville, R. Mooney, and R. Nagarajan, “Content-boosted collaborative filtering for improved recommendations,” presented at the Eighteenth national conference on Artificial intelligence, 2002, pp. 187–192.
描述 碩士
國立政治大學
資訊管理學系
104356017
資料來源 http://thesis.lib.nccu.edu.tw/record/#G0104356017
資料類型 thesis
dc.contributor.advisor 郁方zh_TW
dc.contributor.author (Authors) 鄭巧翊zh_TW
dc.creator (作者) 鄭巧翊zh_TW
dc.date (日期) 2017en_US
dc.date.accessioned 28-Aug-2017 14:16:09 (UTC+8)-
dc.date.available 28-Aug-2017 14:16:09 (UTC+8)-
dc.date.issued (上傳時間) 28-Aug-2017 14:16:09 (UTC+8)-
dc.identifier (Other Identifiers) G0104356017en_US
dc.identifier.uri (URI) http://nccur.lib.nccu.edu.tw/handle/140.119/112280-
dc.description (描述) 碩士zh_TW
dc.description (描述) 國立政治大學zh_TW
dc.description (描述) 資訊管理學系zh_TW
dc.description (描述) 104356017zh_TW
dc.description.abstract (摘要) 社群網路服務在我們的生活中扮演著不可或缺的角色，而其型態也隨著人們的網路使用習慣而改變。我們推導出下一世代的社群網路服務將會圍繞著企業會組織所經營之特定用意的社群，並從自我品牌經營的策略出發，研究輔助虛擬社群成長的各項關鍵服務，經由分析與設計並提出社群廣場之框架。我們的社群廣場結合了內容、社群、交流以及經營自我品牌服務作為關鍵服務，並透過（隱性）標籤鏈結讓虛擬社群中的實體以及服務得以連結。為了評估本研究提出的方法，我們以台灣九所頂尖大學高階工商管理學生（EMBA）的社群為實作對象，開發了一個全新的社群平台9EMBA.COM。初步的調查中顯示，EMBA學生都非常滿意這個社群平台。zh_TW
dc.description.tableofcontents 1 Introduction 1
2 Related Work 3
2.1 The Driving Forces of Virtual Community 3
2.2 Recommendation System 5
2.2.1 Collaborative Filtering 6
2.2.2 Content-based Filtering 6
2.2.3 Hybrid Method 7
3 Adaptive Service Design 7
3.1 Content Service 7
3.2 Community Service 8
3.3 Communication Service 9
3.4 Self-Branding Service 11
4 Adaptive Service Association 12
4.1 Explicit and Implicit Association 13
4.2 Exploration of Entity 13
4.3 Personalized Recommendation of Entity 14
5 Adaptive Social Network 16
6 Implementation: 9EMBA.COM 17
6.1 Progressive Web App 17
6.2 Adaptive Services 19
6.2.1 Communication Service 19
6.2.2 Content Service 26
6.2.3 Recruitment Service 28
6.2.4 Self-Branding Service 32
6.3 Support Layer Modules 32
6.4 Entity Association Network 33
7 Evaluation 36
7.1 Data Gathering 36
7.1.1 In-Depth Interview 36
7.1.2 Questionnaire 37
7.2 Summary 38
8 Conclusion 40
References 40		zh_TW
dc.format.extent 6490083 bytes-
dc.format.mimetype application/pdf-
dc.source.uri (資料來源) http://thesis.lib.nccu.edu.tw/record/#G0104356017en_US
dc.subject (關鍵詞) 社群網路服務zh_TW
dc.subject (關鍵詞) 虛擬社群zh_TW
dc.subject (關鍵詞) 高階經理人管理碩士zh_TW
dc.subject (關鍵詞) Adaptive social networken_US
dc.subject (關鍵詞) Virtual communityen_US
dc.subject (關鍵詞) Executive MBAen_US
dc.title (題名) 自適應社群網路服務：以九校EMBA社群為例zh_TW
dc.title (題名) Adaptive Social Network Services: The Practice of 9EMBA.COMen_US
dc.type (資料類型) thesisen_US
dc.relation.reference (參考文獻) [1] D. M. Boyd and N. B. Ellison, “Social Network Sites: Definition, History, and Scholarship,” Journal of Computer-Mediated Communication, vol. 13, no. 1, pp. 210–230, Oct. 2007.
[2] O. Kwon and Y. Wen, “An empirical study of the factors affecting social network service use,” Computers in Human Behavior, vol. 26, no. 2, pp. 254–263, Mar. 2010.
[3] “MiGente.com — Where Latinos \\& Latinas Meet to Chat, Discuss, Engage.” [Online]. Available: http://www.migente.com/. [Accessed: 21-Feb-2017].
[4] “Featured Content on Myspace.” [Online]. Available: https://myspace.com/. [Accessed: 21-Feb-2017].
[5] “YouTube.” [Online]. Available: https://www.youtube.com/. [Accessed: 21-Feb-2017].
[6] “Instagram,” Instagram. [Online]. Available: https://instagram.com/. [Accessed: 21-Feb-2017].
[7] “Facebook.” [Online]. Available: https://www.facebook.com/. [Accessed: 21-Feb-2017].
[8] “Facebook.” [Online]. Available: https://www.friendster.com/. [Accessed: 21-Feb-2017].
[9] “Pinterest • The world’s catalog of ideas.” [Online]. Available: https://www.pinterest.com/. [Accessed: 21-Feb-2017].
[10] “Yahoo.” [Online]. Available: https://www.yahoo.com/. [Accessed: 21-Feb-2017].
[11] “LinkedIn: Log In or Sign Up.” [Online]. Available: https://www.linkedin.com/. [Accessed: 21-Feb-2017].
[12] “WeChat - Free messaging and calling app.” [Online]. Available: https://www.wechat.com/en/. [Accessed: 21-Feb-2017].
[13] “Twitter. It’s what’s happening.” [Online]. Available: https://twitter.com/?lang=en. [Accessed: 21-Feb-2017].
[14] “9EMBA-HOME.” [Online]. Available: http://9emba.com/articles. [Accessed: 22-Feb-2017].
[15] “Drupal - Open Source CMS | Drupal.org.” [Online]. Available: https://www.drupal.org/. [Accessed: 21-Feb-2017].
[16] “Blog Tool, Publishing Platform, and CMS — WordPress.” [Online]. Available: https://wordpress.org/. [Accessed: 21-Feb-2017].
[17] “The 16 Best Facebook Pages You’ve Ever Seen.” [Online]. Available: https://blog.hubspot.com/blog/tabid/6307/bid/28441/the-15-best-facebook-pages-you-ve-ever-seen.aspx. [Accessed: 14-Feb-2017].
[18] “Starbucks.” [Online]. Available: https://www.facebook.com/Starbucks/. [Accessed: 18-Feb-2017].
[19] “ME MEDIA: Points of View Reference Center Home.” [Online]. Available: http://web.b.ebscohost.com/pov/detail/detail?sid=209cced7-adcf-421d-ba43-f669ae64d40f [Accessed: 14-Feb-2017].
[20] Li, Honglei. "Virtual community studies: A literature review, synthesis and research agenda." AMCIS 2004 Proceedings (2004): 324.
[21] J. Hagel, “Net Gain: Expanding Markets Through Virtual Communities,” Journal of Interactive Marketing (John Wiley \\& Sons), vol. 13, no. 1, pp. 55–65, Winter 1999.
[22] J. Bacon, The Art of Community: Building the New Age of Participation. O’Reilly Media, Inc., 2012.
[23] J. H. Kietzmann, K. Hermkens, I. P. McCarthy, and B. S. Silvestre, “Social media? Get serious! Understanding the functional building blocks of social media,” Business Horizons, vol. 54, no. 3, pp. 241–251, May 2011.
[24] A. Rae, B. Sigurbjörnsson, and R. van Zwol, “Improving Tag Recommendation Using Social Networks,” in Adaptivity, Personalization and Fusion of Heterogeneous Information, Paris, France, France, 2010, pp. 92–99.
[25] “Web,” Google Developers. [Online]. Available: https://developers.google.com/web/progressive-web-apps/. [Accessed: 15-Feb-2017].
[26] M. P. Papazoglou, V. Andrikopoulos, and S. Benbernou, “Managing Evolving Services,” IEEE Software, vol. 28, no. 3, pp. 49–55, May 2011.
[27] S. A. Barab, “An Introduction to the Special Issue: Designing for Virtual Communities in the Service of Learning,” Information Society, vol. 19, no. 3, p. 197, Aug. 2003.
[28] S. Thomaidou and M. Vazirgiannis, “Multiword Keyword Recommendation System for Online Advertising,” in 2011 International Conference on Advances in Social Networks Analysis and Mining, 2011, pp. 423–427.
[29] P. Kazienko, K. Musial, and T. Kajdanowicz, “Multidimensional Social Network in the Social Recommender System,” IEEE Transactions on Systems, Man, and Cybernetics - Part A: Systems and Humans, vol. 41, no. 4, pp. 746–759, Jul. 2011.
[30] C. Marlow, M. Naaman, D. Boyd, and M. Davis, “HT06, Tagging Paper, Taxonomy, Flickr, Academic Article, to Read,” in Proceedings of the Seventeenth Conference on Hypertext and Hypermedia, New York, NY, USA, 2006, pp. 31–40.
[31] S. Ahern, M. Naaman, R. Nair, and J. H.-I. Yang, “World Explorer: Visualizing Aggregate Data from Unstructured Text in Geo-referenced Collections,” in Proceedings of the 7th ACM/IEEE-CS Joint Conference on Digital Libraries, New York, NY, USA, 2007, pp. 1–10.
[32] D. Kempe, J. Kleinberg, and É. Tardos, “Maximizing the Spread of Influence Through a Social Network,” in Proceedings of the Ninth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, New York, NY, USA, 2003, pp. 137–146.
[33] A. S. Das, M. Datar, A. Garg, and S. Rajaram, “Google News Personalization: Scalable Online Collaborative Filtering,” in Proceedings of the 16th International Conference on World Wide Web, New York, NY, USA, 2007, pp. 271–280.
[34] B. Sarwar, G. Karypis, J. Konstan, and J. Riedl, “Item-based Collaborative Filtering Recommendation Algorithms,” in Proceedings of the 10th International Conference on World Wide Web, New York, NY, USA, 2001, pp. 285–295.
[35] M. Deshpande and G. Karypis, “Item-based top-N Recommendation Algorithms,” ACM Trans. Inf. Syst., vol. 22, no. 1, pp. 143–177, Jan. 2004.
[36] A. Salah, N. Rogovschi, and M. Nadif, “A dynamic collaborative filtering system via a weighted clustering approach,” Neurocomputing, vol. 175, pp. 206–215, Jan. 2016.
[37] K. Lang, “NewsWeeder: Learning to Filter Netnews,” in in Proceedings of the 12th International Machine Learning Conference (ML95, 1995.
[38] B. Krulwich and C. Burkey, “The InfoFinder agent: learning user interests through heuristic phrase extraction,” IEEE Expert, vol. 12, no. 5, pp. 22–27, Sep. 1997
[39] W. Hill, L. Stead, M. Rosenstein, and G. Furnas, “Recommending and Evaluating Choices in a Virtual Community of Use,” in Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, New York, NY, USA, 1995, pp. 194–201.
[40] U. Shardanand and P. Maes, “Social Information Filtering: Algorithms for Automating ‘Word of Mouth,’” in Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, New York, NY, USA, 1995, pp. 210–217.
[41] H. Ma, I. King, and M. R. Lyu, “Effective Missing Data Prediction for Collaborative Filtering,” in Proceedings of the 30th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, New York, NY, USA, 2007, pp. 39–46.
[42] P. Melville, R. Mooney, and R. Nagarajan, “Content-boosted collaborative filtering for improved recommendations,” presented at the Eighteenth national conference on Artificial intelligence, 2002, pp. 187–192.		zh_TW