參考文獻 |
英文文獻
[1] Kemp S., “FUTURE FACTORS”, October 11, 2016, available at http://kepios.com/blog/2016/10/11/future-factors
[2] Travers J., Milgram S., “An Experimental Study of the Small World Problem”, Sociometry, Vol. 32, No. 4, pp. 425-443, December 1969.
[3] Bhagat S., Burke M., Diuk C., Fillz I. O., Edunov S., “Three and a half degrees of separation”, February 4 2016, available at https://research.facebook.com/blog/three-and-a-half-degrees-of-separation/
[4] Kincaid J., “EdgeRank: The secret sauce that makes Facebook’s news feed tick”, Techcrunch, April 22, 2010, available at http://techcrunch.com/2010/04/22/facebook-edgerank.
[5] Bucher T,, “Want to be on the top? Algorithmic power and the threat of invisibility on Facebook”, New Media & Society, Vol. 14, Issue 7, pp. 1164-1180, April 2012.
[6] Weber M. S., Monge P., “The flow of digital news in a network of sources, authorities, and hubs”, Journal of Communication, Vol. 61, Vol. 6, Issue 6, pp.1062-1081, December 2011.
[7] Long M. C., Noor Al-Deen H. S., Hendricks J. A. (Eds), Social Media: Usage and Impact, “Beyond the press release: Social media as a tool for consumer engagement”, Lanham, ML: Lexington Books, pp 145-149, 2012.
[8] Allan J., Lavrenko V., Malin D., Swan R., 2000, “Detections, bounds, and timelines: UMass and TDT-3”, Proceedings of Topic Detection and Tracking Workshop, pp. 167–174, 2000.
[9] Shiravi H., Shiravi A., Ghorbani A. A., “A survey of visualization systems for network security”, IEEE Transactions on Visualization and Computer Graphics, Vol. 18, No. 8, pp. 1313-1329, 2012
[10] Fiscus G., Doddington G. R., Allan J. (Ed), Topic Detection and Tracking, Kluwer Academic Publishers, Norwell, MA, USA, pp. 17–31, February 2002.
[11] Zheng Y., Meng Z., Xu C., “A Short-Text Oriented Clustering Method for Hot Topics Extraction”, International Journal of Software Engineering and Knowledge Engineering, Vol. 25, Issue 3, pp. 453, April 2015.
[12] Kaleel S. B., Abhari A., “Cluster-discovery of Twitter messages for event detection and trending,” Journal of Computation Science, Vol. 6, pp. 45-57, January 2015.
[13] Petkos G., Papadopoulos S., Aiello L., Skeaba R., Kompatsiaris Y., “A soft frequent pattern mining approach for textual topic detection”, Proceedings of the 4th International Conference on Web Intelligence, Mining and Semantics, No. 25, June 2014.
[14] Gaglio S., Re G. L., Morana M., “A framework for real-time Twitter data analysis”, Computer Communications, Vol. 73, Part B, pp. 236-242, January 2016.
[15] Song M., Kim M. C., Jeong Y. K., “Analyzing the Political Landscape of 2012 Korean Presidential Election in Twitter”, Intelligent System, IEEE, Vol. 29, Issue 2, pp. 18-26, March 2014.
[16] Cleary I., “Facebook Analytics: The Only Guide You’ll Ever Need”, RAZORSOCIAL, June 9, 2017, available at http://www.razorsocial.com/facebook-analytics-reference-guide/.
[17] Christopher H., “Brands Favor Social Shares Over Likes”, ADWEEK, April 1, 2013, available at http://www.adweek.com/news/advertising-branding/brands-favor-social-shares-over-likes-148256.
[18] Fung G. P. C., Yu J. X. Y., Yu P. S., Lu H., “Parameter free bursty events detection in text streams”, Proceeding of the VLDB: 31st Int. Conf. Very Large Data Bases, pp. 181–192, August 2005.
[19] Yang Y., Pierce T., Carbonell J., “A study of retrospective and on-line event detection”, Proceedings of the 21st Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, Melbourne, pp. 28–36, August 1998.
[20] Brants T., Chen F., Farachar A., “A system for new event detection”, Proceedings of the 26th Annual International ACM SIGIR Conference on Research and Development in information Retrieval, pp. 330-337, August 2003.
[21] Cilibrasi R. L., Vitanyi P., “The google similarity distance”, IEEE Transactions on Knowledge and Data Engineering, Vol. 19, No.3, pp. 370-383, March 2007.
[22] Makrehchi M., Kamel M. S., “Automatic Taxonomy Extraction Using Google and Term Dependency”, IEEE/WIC/ACM International Conference on Web Intelligence, pp. 321-325, 2007.
[23] Woon W. L., Madnick S., “Asymmetric information distances for automated taxonomy construction”, Knowledge and information systems, Vol. 21, Vol. 1, Issue 1, pp. 91-111, October 2009.
[24] Mikolov T., Chen K., Corrado G., et al., “Efficient Estimation of Word Representations in Vector Space”, Computer Science, pp. 28-36, Jan 2013.
[25] Li Y., McLean D., Bandar Z. A., O’Shea J. D., Crockett L., “Sentence Similarity Based on Semantic Nets and Corpus Statistics”, IEEE Transaxtions on Knowledge and Data Engineering, Vol. 18, Issue 8, pp 1138-1150, June 2006.
[26] Kaufman L., Rousseeuw P. J., “Clustering by means of Medoids.,” pp. 405–416, 1987.
中文文獻
[27] 傅珮雯,「Facebook 網站上口碑行為之研究」,國立中山大學,企業管理學系碩士論文,民國100年。
[28] Fukuball,結巴中文分詞,jieba-0.25,取自 https://github.com/fukuball/jieba-php。
[29] 唐鳳,萌典,取自 https://www.moedict.tw/about.html。
[30] 中研院,中文斷詞系統,取自 http:// ckipsvr.iis.sinica.edu.tw/。
[31] 鄭奕駿,「離線搜尋 Wikipedia 以縮減 NGD 運算時間之研究」,國立中央大學,資訊管理學系碩士論文,民國101年。
[32] Word2Vec中的數學原理詳解,取自http://blog.csdn.net/itplus/article/details/37969519。
[33] 郭海蓉、張暉,「增量劇類在動太多文檔摘要中的研究與應用」,中國西南科技大學,西元2012年。
[34] 林熙禎、侯貫中、張昇暉、趙濬、陳棅、郭台達,「資料視覺化在社群媒體下議題追蹤的應用」,TANET 台灣網際網路研討會,883-888頁,2016。
[35] Wikipedia資料集,20161120更新,取自https://dumps.wikimedia.org/zhwiki/。 |