博碩士論文 103421043 詳細資訊




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姓名 魏天昊(Tien-Hao Wei)  查詢紙本館藏   畢業系所 企業管理學系
論文名稱 特殊事件發生期間產生之情緒效應對微網誌產品推薦效果之影響
(The Effect of Event Sentiment on Product Recommendation in a Microblog Platform)
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摘要(中) 中文摘要
特殊事件的發生和人類情緒之間有著緊密的關聯性,情緒字詞是人們用來有效描述特殊事件的重要媒介(Kolya et al., 2011),社群網站的使用者情緒會因為現實世界中特殊事件的發生而產生明顯差異(Kramer, 2010; Choudhury et al., 2008)。透過社群網站所蘊含的大量情緒成分,本研究針對事件情緒、發文情緒和產品推薦情緒進行探討,並分析如何利用情緒變數來引起使用者對於產品推薦的點擊興趣。
為了解情緒如何影響推薦效果,本研究使用微網誌平台Plurk配合卓淑玲、陳學志、鄭昭明(2013)的中文情緒詞庫,以情緒關鍵字為根據來判斷使用者的發文情緒,同時利用情緒字詞為產品推薦的依據,並且進一步透過T檢定、one-way Anova、two-way Anova探討不同情緒變數對於產品推薦效果的影響。
由實驗結果發現,在正向事件的影響下,微網誌使用者的負向情緒發文會比正向發文更能夠提升產品推薦效果。在帶有不同情緒字詞的產品推薦中,正向情緒推薦比起負向和中立推薦更能達到推薦效果的提升。除此之外,在負向發文底下予以正向情緒的產品推薦能帶來最佳的產品推薦效果。另一方面,在負向事件的影響下,微網誌使用者的負向情緒發文會比正向發文更能夠提升產品推薦效果。在帶有不同情緒字詞的產品推薦中,負向情緒推薦比起正向和中立推薦更能達到推薦效果的提升。除此之外,在負向發文底下予以負向情緒的產品推薦能夠帶來最佳的產品推薦效果。
藉由本研究的結果,能有效幫助服務或產品供應商在特殊事件發生期間進行社群行銷,以利用情緒變數的方式有效吸引社群網站用戶對廣告的點擊興趣,進而達到提升產品推薦效果的目標。
摘要(英) Sentiment and Event are two abstract entities closely coupled with each other. Sentiment terms are important medium that people can describe events(Kolya et al., 2011). The occurring of events will bring significant difference in user sentiment of social media(Kramer, 2010; Choudhury et al., 2008).Through the sentiment component of social media, our research focus on the sentiment of event, user posts and product recommendation. We analyze sentiment variables and discuss how to arouse user attention in order to improve the effectiveness of social marketing.
In order to realize the influence of sentiment, we apply the microblog platform Plurk in line with Chinese sentiment lexicon provided by Jhuo et al. (2013). Based on sentiment lexicon, we extract and classify user sentiment according to sentiment keywords emerge in posts. Apart from this, we use the lexicon as foundation of product recommendation to observe the influence of sentiment words.
Under the influence of positive event, our results show that negative posts and positive recommendation are more effective to product recommendation. Besides, negative recommendation under the positive posts will bring the most effective outcome. On the other hand, under the influence of negative event, our results show that negative posts and negative recommendation are more effective to product recommendation. Besides, negative recommendation under the negative posts will bring the most effective outcome.
Through the experiment results, service or product suppliers can use sentiment variables on social marketing during event period to achieve better quality of product recommendation.
關鍵字(中) ★ 特殊事件
★ 情緒
★ 微網誌
★ Plurk
★ 產品推薦
關鍵字(英) ★ event
★ sentiment
★ microblog
★ Plurk
★ product recommendation
論文目次 中文摘要 i
Abstract ii
目錄 iii
表目錄 v
圖目錄 vi
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 研究架構 4
第二章 文獻探討 6
2.1 特殊事件與情緒效應 6
2.2 社群網站與社群行銷 7
2.3 情緒與心理學理論 9
2.4情緒分析與情緒詞庫 11
第三章 研究方法 13
3.1社群平台-Plurk 13
3.2 資料收集 14
3.3 產品推薦方法 16
3.4研究假設 18
3.5變數及分析方法說明 24
3.5.1變數說明 24
3.5.2分析方法 27
第四章 研究實作 30
4.1 資料分析 30
4.1.1 資料前處理 30
4.1.2 實驗結果 30
4.1.3 假設結果討論 39
4.2 後續探討 40
4.2.1 不顯著假設之探討 40
4.2.2 分析結果之探討 42
4.2.3 無事件情緒下之探討 43
第五章 結論與未來研究建議 45
5.1研究結論 45
5.2研究貢獻 45
5.3研究限制及未來研究建議 47
參考文獻 48
附錄一:情緒描述詞的六個向度分數-218個(部分範例) 57
附錄二:情緒誘發詞的四個向度分數-395個(部分範例) 58
參考文獻 [1] Asch, Solomon E. "Studies of independence and conformity: I. A minority of one against a unanimous majority." Psychological monographs: General and applied 70.9 (1956): 1.
[2] Bakshy, Eytan, et al. "Everyone′s an influencer: quantifying influence on twitter." Proceedings of the fourth ACM international conference on Web search and data mining. ACM, (2011).
[3] Balahur, Alexandra, and Ralf Steinberger. "Rethinking Sentiment Analysis in the News: from Theory to Practice and back." Proceeding of WOMSA 9 (2009).
[4] Balahur, Alexandra, Jesús M. Hermida, and AndréS Montoyo. "Detecting implicit expressions of emotion in text: A comparative analysis." Decision Support Systems 53.4 (2012): 742-753.
[5] Banerjee, Nilanjan, et al. "User interests in social media sites: an exploration with micro-blogs." Proceedings of the 18th ACM conference on Information and knowledge management. ACM, (2009).
[6] Bartsch, Anne, Markus Appel, and Dennis Storch. "Predicting emotions and meta-emotions at the movies: The role of the need for affect in audiences’ experience of horror and drama." Communication Research 37.2 (2010): 167-190.
[7] Bavelas, Janet Beavin, et al. "14 Motor mimicry as primitive empathy." Empathy and its development (1990): 317.
[8] Bermingham, Adam, and Alan F. Smeaton. "On using Twitter to monitor political sentiment and predict election results." (2011).
[9] Berridge, Kent C. "Pleasures of the brain." Brain and cognition 52.1 (2003): 106-128.
[10] Bimber, Bruce. "The Internet and political transformation: Populism, community, and accelerated pluralism." Polity (1998): 133-160.
[11] Bimber, Bruce. "The study of information technology and civic engagement." Political Communication 17.4 (2000): 329-333.
[12] Brosch, Tobias, Gilles Pourtois, and David Sander. "The perception and categorisation of emotional stimuli: A review." Cognition and Emotion 24.3 (2010): 377-400.
[13] Knobloch, Silvia. "Suspense and mystery." (2003).
[14] Carver, Charles S., and Teri L. White. "Behavioral inhibition, behavioral activation, and affective responses to impending reward and punishment: the BIS/BAS scales." Journal of personality and social psychology 67.2 (1994): 319.
[15] Cha, Meeyoung, et al. "Measuring User Influence in Twitter: The Million Follower Fallacy." ICWSM 10.10-17 (2010): 30.
[16] Chen, Yen-Liang, Li-Chen Cheng, and Ching-Nan Chuang. "A group recommendation system with consideration of interactions among group members." Expert systems with applications 34.3 (2008): 2082-2090.
[17] Chiu, Chao-Min, Meng-Hsiang Hsu, and Eric TG Wang. "Understanding knowledge sharing in virtual communities: An integration of social capital and social cognitive theories." Decision support systems 42.3 (2006): 1872-1888.
[18] Christensen, Ingrid A., and Silvia Schiaffino. "Entertainment recommender systems for group of users." Expert Systems with Applications 38.11 (2011): 14127-14135.
[19] Church, Timothy, et al. "Language and organisation of Filipino emotion concepts: comparing emotion concepts and dimensions across cultures." Cognition & emotion 12.1 (1998): 63-92.
[20] Cornfield, Michael. "New and improved. " Campaign & Elections 25 (2004): 42.
[21] Davis, Mark R. "Perceptual and affective reverberation components." Empathy: Development, training, and consequences (1985): 62-108.
[22] De Choudhury, Munmun, et al. "Multi-scale characterization of social network dynamics in the blogosphere." Proceedings of the 17th ACM conference on Information and knowledge management. ACM, (2008).
[23] Delli Carpini, Michael X. "Gen.com: Youth, civic engagement, and the new information environment." Political communication 17.4 (2000): 341-349.
[24] Delre, Sebastiano A., et al. "Will it spread or not? The effects of social influences and network topology on innovation diffusion." Journal of Product Innovation Management 27.2 (2010): 267-282.
[25] Diakopoulos, Nicholas A., and David A. Shamma. "Characterizing debate performance via aggregated twitter sentiment." Proceedings of the SIGCHI Conference on Human Factors in Computing Systems. ACM, (2010).
[26] Dong, Ruihai, et al. "Opinionated product recommendation." Case-Based Reasoning Research and Development. Springer Berlin Heidelberg, (2013). 44-58.
[27] Esparza, Sandra Garcia, Michael P. O’Mahony, and Barry Smyth. "Mining the real-time web: a novel approach to product recommendation." Knowledge-Based Systems 29 (2012): 3-11.
[28] Esuli, Andrea, and Fabrizio Sebastiani. "Sentiwordnet: A publicly available lexical resource for opinion mining." Proceedings of LREC. Vol. 6. (2006).
[29] Fontaine, Johnny RJ, et al. "The world of emotions is not two-dimensional." Psychological science 18.12 (2007): 1050-1057.
[30] Fredrickson, Barbara L., and Christine Branigan. "Positive emotions broaden the scope of attention and thought‐action repertoires." Cognition & emotion 19.3 (2005): 313-332.
[31] Galati, Dario, et al. "The lexicon of emotion in the neo-Latin languages." Social science information 47.2 (2008): 205-220.
[32] Gehm, Theodor L., and Klaus R. Scherer. "Factors determining the dimensions of subjective emotional space." (1988).
[33] Gillin, Paul. "Secrets of Social Media Marketing: How to Use Online Conversations and Customer Communities to Turbo-charge Your Business!" Linden Publishing, (2008).
[34] Goleman, D. "EQ—Emotional Intelligence." (1995).
[35] Hartmann, Tilo, and Peter Vorderer. "It′s okay to shoot a character: Moral disengagement in violent video games." Journal of Communication 60.1 (2010): 94-119.
[36] Hatfield, Elaine, John T. Cacioppo, and Richard L. Rapson. "Emotional contagion." Cambridge university press, (1994).
[37] Higgins, E. Tory, James Shah, and Ronald Friedman. "Emotional responses to goal attainment: strength of regulatory focus as moderator." Journal of personality and social psychology 72.3 (1997): 515.
[38] Hill, Shawndra, Foster Provost, and Chris Volinsky. "Network-based marketing: Identifying likely adopters via consumer networks." Statistical Science (2006): 256-276.
[39] Hong, Liangjie, Ovidiu Dan, and Brian D. Davison. "Predicting popular messages in twitter." Proceedings of the 20th international conference companion on World wide web. ACM, (2011).
[40] Howard, Daniel J., and Charles Gengler. "Emotional contagion effects on product attitudes." Journal of Consumer research 28.2 (2001): 189-201.
[41] Hu, Minqing, and Bing Liu. "Mining opinion features in customer reviews." AAAI. Vol. 4. No. 4. (2004).
[42] Hu, Wei. "Real-Time Twitter Sentiment toward Thanksgiving and Christmas Holidays." (2013).
[43] Huffaker, David. "Dimensions of leadership and social influence in online communities." Human Communication Research 36.4 (2010): 593-617.
[44] Java, Akshay, et al. "Why we twitter: understanding microblogging usage and communities." Proceedings of the 9th WebKDD and 1st SNA-KDD 2007 workshop on Web mining and social network analysis. ACM, (2007).
[45] Jeppson, Kjell O., and Christer M. Svensson. "Negative bias stress of MOS devices at high electric fields and degradation of MNOS devices." Journal of Applied Physics 48.5 (1977): 2004-2014.
[46] Johnson, Stefanie K. "I second that emotion: Effects of emotional contagion and affect at work on leader and follower outcomes." The Leadership Quarterly 19.1 (2008): 1-19.
[47] Johnson-Laird, Philip Nicholas, and Keith Oatley. "The language of emotions: An analysis of a semantic field." Cognition and emotion 3.2 (1989): 81-123.
[48] Joyce, Elisabeth, and Robert E. Kraut. "Predicting continued participation in newsgroups." Journal of Computer‐Mediated Communication 11.3 (2006): 723-747.
[49] Kaid, Lynda Lee, and Anne Johnston. "Videostyle in presidential campaigns: Style and content of televised political advertising." Greenwood Publishing Group, (2001).
[50] Kim, Elsa, et al. "Detecting sadness in 140 characters: Sentiment analysis of mourning michael jackson on twitter." Web Ecology 3 (2009): 1-15.
[51] Kim, Hongki, Kil-Soo Suh, and Un-Kon Lee. "Effects of collaborative online shopping on shopping experience through social and relational perspectives." Information & Management 50.4 (2013): 169-180.
[52] Kim, Youngseek, Minjae Kim, and Kyungseek Kim. "Factors influencing the adoption of social media in the perspective of information needs." (2010).
[53] Kiss, Christine, and Martin Bichler. "Identification of influencers—measuring influence in customer networks." Decision Support Systems 46.1 (2008): 233-253.
[54] Kleinginna Jr, Paul R., and Anne M. Kleinginna. "A categorized list of emotion definitions, with suggestions for a consensual definition." Motivation and emotion 5.4 (1981): 345-379.
[55] Kolya, Anup Kumar, et al. "Identifying event: sentiment association using lexical equivalence and co-reference approaches." Proceedings of the ACL 2011 Workshop on Relational Models of Semantics. Association for Computational Linguistics, (2011).
[56] Kouloumpis, Efthymios, Theresa Wilson, and Johanna D. Moore. "Twitter sentiment analysis: The good the bad and the omg!" Icwsm 11 (2011): 538-541.
[57] Kramer, Adam DI. "An unobtrusive behavioral model of gross national happiness." Proceedings of the SIGCHI conference on human factors in computing systems. ACM, (2010).
[58] Kwak, Haewoon, et al. "What is Twitter, a social network or a news media?" Proceedings of the 19th international conference on World Wide Web. ACM, (2010).
[59] Labroo, Aparna A., and Derek D. Rucker. "The orientation-matching hypothesis: An emotion-specificity approach to affect regulation." Journal of Marketing Research 47.5 (2010): 955-966.
[60] Lang, Annie, Deborah Potter, and Maria Elizabeth Grabe. "Making news memorable: Applying theory to the production of local television news." Journal of Broadcasting & Electronic Media 47.1 (2003): 113-123.
[61] Lang, Annie. "Using the limited capacity model of motivated mediated message processing to design effective cancer communication messages." Journal of Communication 56.s1 (2006): S57-S80.
[62] Lee, Sophia Yat Mei, Ying Chen, and Chu-Ren Huang. "A text-driven rule-based system for emotion cause detection." Proceedings of the NAACL HLT 2010 Workshop on Computational Approaches to Analysis and Generation of Emotion in Text. Association for Computational Linguistics, (2010).
[63] Levy, Steven. "Dean’s net effect is just the start." Newsweek 143 (2004): 73.
[64] Li, Dongsheng, et al. "Interest-based real-time content recommendation in online social communities." Knowledge-Based Systems 28 (2012): 1-12.
[65] Li, Feng, and Timon C. Du. "Who is talking? An ontology-based opinion leader identification framework for word-of-mouth marketing in online social blogs." Decision Support Systems 51.1 (2011): 190-197.
[66] Li, Yung-Ming, and Ching-Wen Chen. "A synthetical approach for blog recommendation: Combining trust, social relation, and semantic analysis." Expert Systems with Applications 36.3 (2009): 6536-6547.
[67] Li, Yung-Ming, and Nine-Jun Lien. "An endorser discovering mechanism for social advertising." Proceedings of the 11th International Conference on Electronic Commerce. ACM, (2009).
[68] Li, Yung-Ming, and Ya-Lin Shiu. "A diffusion mechanism for social advertising over microblogs." Decision Support Systems 54.1 (2012): 9-22.
[69] Malatesta, G. "Conformity rules in cyberspace." The Australian (2001): 40.
[70] McLeod, Jack M., and Lee B. Becker. "The uses and gratifications approach." Handbook of political communication (1981): 67-99.
[71] McPherson, Miller, Lynn Smith-Lovin, and James M. Cook. "Birds of a feather: Homophily in social networks." Annual review of sociology (2001): 415-444.
[72] McQuail, Denis, Jay G. Blumler, and John R. Brown. "The television audience: A revised perspective." Media studies: A reader 271 (1972): 284.
[73] Mehrabian, Albert, and James A. Russell. "An approach to environmental psychology." the MIT Press, (1974).
[74] Mohammad, Saif M., et al. "Sentiment, emotion, purpose, and style in electoral tweets." Information Processing & Management 51.4 (2015): 480-499.
[75] Nasukawa, Tetsuya, and Jeonghee Yi. "Sentiment analysis: Capturing favorability using natural language processing." Proceedings of the 2nd international conference on Knowledge capture. ACM, (2003).
[76] Naveed, Nasir, et al. "Bad news travel fast: A content-based analysis of interestingness on twitter." Proceedings of the 3rd International Web Science Conference. ACM, (2011).
[77] Oliver, Mary Beth. "Exploring the paradox of the enjoyment of sad films." Human Communication Research 19.3 (1993): 315-342.
[78] O′Mahony, Michael P., and Barry Smyth. "Learning to recommend helpful hotel reviews." Proceedings of the third ACM conference on Recommender systems. ACM, (2009).
[79] Ortony, Andrew, Gerald L. Clore, and Allan Collins. "The cognitive structure of emotions. " Cambridge university press, (1990).
[80] Pak, Alexander, and Patrick Paroubek. "Twitter as a Corpus for Sentiment Analysis and Opinion Mining." LREc. Vol. 10. (2010).
[81] Pang, Bo, Lillian Lee, and Shivakumar Vaithyanathan. "Thumbs up?: sentiment classification using machine learning techniques." Proceedings of the ACL-02 conference on Empirical methods in natural language processing-Volume 10. Association for Computational Linguistics, (2002).
[82] Pennebaker, James W., Matthias R. Mehl, and Kate G. Niederhoffer. "Psychological aspects of natural language use: Our words, our selves." Annual review of psychology 54.1 (2003): 547-577.
[83] Popescu, Ana-Maria, and Marco Pennacchiotti. "Detecting controversial events from twitter." Proceedings of the 19th ACM international conference on Information and knowledge management. ACM, (2010).
[84] Popescu, Ana-Maria, Marco Pennacchiotti, and Deepa Paranjpe. "Extracting events and event descriptions from twitter." Proceedings of the 20th international conference companion on World Wide Web. ACM, (2011).
[85] Posner, Jonathan, James A. Russell, and Bradley S. Peterson. "The circumplex model of affect: An integrative approach to affective neuroscience, cognitive development, and psychopathology." Development and psychopathology 17.03 (2005): 715-734.
[86] Qiu-dan, SONG Shuang-yong LI, and L. U. Dong-yuan. "Hot Event Sentiment Analysis Method in Micro-blogging." Computer Science (2012): S1.
[87] Romero, Daniel M., et al. "Influence and passivity in social media." Machine learning and knowledge discovery in databases. Springer Berlin Heidelberg, (2011). 18-33.
[88] Roseman, Ira J. "Cognitive determinants of emotion: A structural theory." Review of personality & social psychology (1984).
[89] Roseman, Ira J., and Craig A. Smith. "Appraisal theory: Overview, assumptions, varieties, controversies." (2001).
[90] Russell, James A. "Pancultural aspects of the human conceptual organization of emotions." Journal of personality and social psychology 45.6 (1983): 1281.
[91] Russell, James A., and James M. Carroll. "On the bipolarity of positive and negative affect." Psychological bulletin 125.1 (1999): 3.
[92] Scherer, K., and H. Wallbott. "The ISEAR questionnaire and codebook." Geneva Emotion Research Group (1997).
[93] Scherer, Klaus R. "Appraisal considered as a process of multilevel sequential checking." Appraisal processes in emotion: Theory, methods, research 92 (2001): 120.
[94] Scherer, Klaus R., Angela Schorr, and Tom Johnstone, eds. "Appraisal processes in emotion: Theory, methods, research." Oxford University Press, (2001).
[95] Schroder, Dieter K., and Jeff A. Babcock. "Negative bias temperature instability: Road to cross in deep submicron silicon semiconductor manufacturing." Journal of Applied Physics 94.1 (2003): 1-18.
[96] Schumaker, Robert P., et al. "Evaluating sentiment in financial news articles." Decision Support Systems 53.3 (2012): 458-464.
[97] Schwarz, Norbert, and Gerald L. Clore. "Feelings and phenomenal experiences." Social psychology: Handbook of basic principles 2 (1996): 385-407.
[98] Shaver, Phillip R., Upekkha Murdaya, and R. Chris Fraley. "Structure of the Indonesian emotion lexicon." Asian journal of social psychology 4.3 (2001): 201-224.
[99] Small, Deborah A., and Nicole M. Verrochi. "The face of need: Facial emotion expression on charity advertisements." Journal of Marketing Research 46.6 (2009): 777-787.
[100] Smith, Craig A., and Phoebe C. Ellsworth. "Patterns of cognitive appraisal in emotion." Journal of personality and social psychology 48.4 (1985): 813.
[101] Soroka, Stuart N. "Negativity in democratic politics: Causes and consequences." Cambridge University Press, (2014).
[102] Sparks, Glenn G., and Cheri W. Sparks. "Violence, mayhem, and horror." Media entertainment: The psychology of its appeal (2000): 73-92.
[103] Sun, Aaron R., Jiesi Cheng, and Daniel Dajun Zeng. "A novel recommendation framework for micro-blogging based on information diffusion." 19th Annual Workshop on Information Technolgies & Systems (WITS′09). (2009).
[104] Taboada, Maite, et al. "Lexicon-based methods for sentiment analysis." Computational linguistics 37.2 (2011): 267-307.
[105] Talmy, Leonard. "Toward a cognitive semantics, Volume 1: Concept structuring systems (language, speech, and communication)." (2003).
[106] Thelwall, Mike, Kevan Buckley, and Georgios Paltoglou. "Sentiment in Twitter events." Journal of the American Society for Information Science and Technology 62.2 (2011): 406-418.
[107] Turney, Peter D. "Thumbs up or thumbs down?: semantic orientation applied to unsupervised classification of reviews." Proceedings of the 40th annual meeting on association for computational linguistics. Association for Computational Linguistics, (2002).
[108] Vorderer, Peter, Christoph Klimmt, and Ute Ritterfeld. "Enjoyment: At the heart of media entertainment." Communication theory 14.4 (2004): 388-408.
[109] Vorderer, Peter. "It′s all entertainment—sure. But what exactly is entertainment? Communication research, media psychology, and the explanation of entertainment experiences." Poetics 29.4 (2001): 247-261.
[110] Wang, Kai-Yu, I-Hsien Ting, and Hui-Ju Wu. "Discovering interest groups for marketing in virtual communities: An integrated approach." Journal of Business Research 66.9 (2013): 1360-1366.
[111] Weng, Jianshu, et al. "Twitter rank: finding topic-sensitive influential twitterers." Proceedings of the third ACM international conference on Web search and data mining. ACM, (2010).
[112] Whitelaw, Casey, Navendu Garg, and Shlomo Argamon. "Using appraisal groups for sentiment analysis." Proceedings of the 14th ACM international conference on Information and knowledge management. ACM, (2005).
[113] Wilson, Theresa, Janyce Wiebe, and Paul Hoffmann. "Recognizing contextual polarity in phrase-level sentiment analysis." Proceedings of the conference on human language technology and empirical methods in natural language processing. Association for Computational Linguistics, (2005).
[114] Wolf, Gary. "Weapons of mass mobilization." Wired 12.09 (2004): 1–8.
[115] Yoshida, Masaaki, et al. "Multi-dimensional scaling of emotion." Japanese psychological research 12.2 (1970): 45-61.
[116] Zhao, Jichang, et al. "Moodlens: an emoticon-based sentiment analysis system for chinese tweets." Proceedings of the 18th ACM SIGKDD international conference on Knowledge discovery and data mining. ACM, (2012).
[117] Zhao, Qiankun, Prasenjit Mitra, and Bi Chen. "Temporal and information flow based event detection from social text streams." AAAI. Vol. 7. (2007).
[118] Zillmann, Dolf, and Peter Vorderer, eds. "Media entertainment: The psychology of its appeal." Routledge, (2000).
[119] 台灣人口數統計 by 中華民國統計資訊網 Retrieved April.15, 2016, from http://www.stat.gov.tw/mp.asp?mp=4
[120] 印度人口數統計 by 人口時鐘 Retrieved April.15, 2016, from http://countrymeters.info/cn/India
[121] 吳明隆. "SPSS 操作與應用: 問卷統計分析實務." 五南圖書出版股份有限公司, (2007).
[122] 李德治 & 童惠玲. "多變量分析: 專題及論文常用的統計方法." 雙葉書廊(2009).
[123] 卓淑玲, 陳學志, and 鄭昭明. "台灣地區華人情緒與相關心理生理資料庫—中文情緒詞常模研究." Chinese Journal of Psychology 55.4 (2013): 493-523.
[124] 林聰吉. "解析台灣民眾的反政黨情緒." (2013): 47-72.
[125] 邱皓政. "量化研究與統計分析:SPSS中文視窗版資料分析範例解析." 台北:五南(2002).
[126] 張永翔. "SPSS統計分析實例寶典" (2002) Retrieved April.26, 2016, from http://w3.thvs.tp.edu.tw/th5001/B/p5.doc
[127] 梁爱州. "当代中国公民网络政治参与的现状及对策研究." MS thesis. 西北师范大学, (2011).
[128] 陳皎眉 & 楊家雯. "情緒調節與情緒管理." T&D飛訊,81,1-18, (2009).
[129] 廖登豪. "微網誌使用者發文情緒對產品推薦效果之影響." (2015)
[130] 榮泰生. "SPSS 與研究方法." 五南圖書出版股份有限公司, (2006).
[131] 噗浪使用者分佈-Plurk Site Overview by alexa (2016) Retrieved April.14, 2016, from http://www.alexa.com/siteinfo/plurk.com
[132] 數位時代. "網路產業誰領風騷? 2015台灣百大熱門網站揭曉! " (2015) Retrieved April.14, 2016, from http://www.bnext.com.tw/article/view/id/35475
[133] 蔡秀玲 & 楊智馨. "情緒管理." 台北: 揚智 (1999).
[134] 聯合新聞網. "為何百萬鐵粉 愛噗浪勝於臉書…" (2015) Retrieved April.14, 2016, from http://udn.com/news/story/7087/782456-為何百萬鐵粉-愛噗浪勝於臉書…
[135] 陈昕 & 高霏霏. "浅析我国公民网络政治参与的问题及对策." 江西科技师范学院学报 7.1 (2012): 5-7.
指導教授 許秉瑜(Ping-Yu Hsu) 審核日期 2016-6-20
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