進階搜尋


下載電子全文  
系統識別號 U0026-2008201414453600
論文名稱(中文) 幸福促進之基於調適過程模型情感偵測及回饋系統
論文名稱(英文) An Emotional Feedback System Based on a Regulation Process Model for Happiness Improvement
校院名稱 成功大學
系所名稱(中) 電機工程學系
系所名稱(英) Department of Electrical Engineering
學年度 102
學期 2
出版年 103
研究生(中文) 洪宇衡
研究生(英文) Yu-Heng Hung
學號 N26004731
學位類別 碩士
語文別 英文
論文頁數 62頁
口試委員 指導教授-王駿發
口試委員-王家慶
口試委員-吳宗憲
口試委員-陳璽煌
口試委員-林博川
中文關鍵字 自然語言處理  社群網路  支援向量機  情感調節 
英文關鍵字 Natural Language Processing (NLP)  Social Network  Support Vector Machine (SVM)  Emotion Regulation 
學科別分類
中文摘要 本篇論文中,一個基於調節過程模型的整合情感調節系統(IERS)被提出應用於提升幸福感。除了從使用者在社群網站中的內容解析出有價值的資訊外,IERS分析了使用者的情感變化將其對應到調節過程模型,並且針對這些情感變化適當給使用者回饋。我們從調節語料庫中選擇正面且激勵的回饋文字。本篇提出的IERS除了工作在單字層級的運算外,對於從Facebook塗鴉牆上收集的語料,採用支援向量基進行情緒主題的分類;同時回饋策略的選擇是由點對點相互資訊的特徵擷取決定。對於本篇七個情緒類別的辨認精準度可以達到超過50%。在20個受試者參與一周的實驗中,藉由觀察實驗的前測與後測結果,可以發現本篇提出的系統確實能夠提升幸福感。
英文摘要 In this thesis, an integrated emotion regulation system (IERS) is proposed based on the regulation process model for happiness improvement. Including extracting the valuable information from user’s contents on social network, the IERS analyzes users’ emotion variation reflecting to the regulation process model and aim to appropriately feedback to users. The feedback sentences are chosen from regulation corpus which is positive and motivated. The proposed IERS works at the word level and the emotional topics is classified by Support vector machine (SVM) through the corpus collected from Facebook wall, whereas feedback strategy is chosen through Point-Wise Mutual Information (PMI) features extraction. The accuracy result of seven-type emotion recognition can achieve higher than 50%. The pre- and post-experiment results are evaluated by 20 participants in one week of observation, of which the result implies the proposed system can practically improve the happiness.
論文目次 中文摘要 I
Abstract II
誌謝 III
Content IV
Table List VI
Figure List VII
Chapter 1 Introduction 1
1.1 Background 1
1.2 Motivation and Contribution 2
1.3 Related Works 4
1.4 Organization 5
Chapter 2 Basis for Emotion Regulation System 7
2.1 Social Network Research 7
2.1.1 Social Network Data Mining 8
2.1.2 Psychology research on Facebook 8
2.2 Computer-Aided Behavior Changing 9
2.2.1 Emotion control research 9
2.2.2 Persuasive Technology 9
2.3 Emotion Regulation Theory 10
2.3.1 Different kinds of psychology strategy comparison 11
2.3.2 Emotion regulation theory 12
Chapter 3 Integrated Emotion Regulation System (IERS) 15
3.1 Architecture Overview 15
3.2 Pre-processing 16
3.3 Point-Wise Mutual Information (PMI) 18
3.4 Support Vector Machines (SVM) 20
3.5 Emotion Regulation Process Model 21
3.5.1 Emotion category selection 21
3.5.2 Traits of user habits for regulation parameters 23
3.5.2.1 Active or passive 23
3.5.2.2 Friend interaction habits 24
3.5.2.3 Emotion processing status 25
3.5.3 Emotion regulation strategy and algorithm 25
3.6 IERS system construction 30
Chapter 4 Experiments and Results 33
4.1 Experiment Tool and Settings 33
4.2 Corpus 33
4.3 Evaluation Method and Environment 37
4.4 Experiment Results 38
4.4.1 Emotion recognition 38
4.4.2 Emotion regulation evaluation 40
Chapter 5 Conclusions and Future Works 45
5.1 Conclusions 45
5.2 Limitations and Future Works 45
References 46
Appendix-A Satisfaction with Life Scale (SWLS) 52
Appendix-B The Positive and Negative Affect Schedule (PANAS) Questionnaire 53
Appendix-C Emotion Regulation Questionnaire (ERQ) 55
Appendix-D Subjective Happiness Scale (SHS) 57
Appendix-E Mean Opinion Score (MOS) 59
Appendix-F Emotion Regulation Feedback Example 60
F.1 Sentence 60
F.2 Question 60
F.3 Action 61
F.3.1 Responsibility Transfer 61
F.3.2 Rewriting Reality 61
參考文獻 [1] M. Burke, C. Marlow, T. Lento, “Social Network Activity and Social Well-Being,” CHI '10 Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, pp. 1909-1912, ACM New York, NY, USA, 2010.
[2] Mr. Fex. (2014, Feb.). Charlotte Dawson Commits Suicide: Australian Model Killed Self Over Twitter Bullying [Online]. Available: http://fexcamp.com/charlotte-dawson-commits-suicide-australian-model-killedself-over-twitter-bullying/#.U2skv_mSwmM
[3] E. Kouloumpis, T. Wilson, and J. Moore, "Twitter sentiment analysis: The good the bad and the omg!," In Proc. of the 5th International AAAI Conference on Weblogs and Social Media, pp. 538-541, 2011.
[4] C. Ma, A. Osherenko, H. Prendinger, and M. Ishizuka, “A Chat System Based on Emotion Estimation from Text and Embodied Conversational Messengers,” Proc. 2005 Int’l Conf. Active Media Technology, pp. 546-548, 2005.
[5] X. Jin, et al. "Sensitive webpage classification for content advertising," Proceedings of the 1st international workshop on Data mining and audience intelligence for advertising, ACM, pp. 28-33, 2007.
[6] J. J. Gross and R. A. Thompson, "Emotion regulation: Conceptual foundations," in Handbook of Emotion Regulation, New York: Guilford Press, 2007, pp. 3-26.
[7] B. Pang and L. Lee, “Opinion Mining and Sentiment Analysis,” Foundations and Trends in Information Retrieval, vol. 2, pp. 1-135, 2008.
[8] R.A. Calvo and S.D. Mello, “Affect Detection: An Interdisciplinary Review of Models, Methods and Their Applications,” IEEE Trans. Affective Computing, vol. 1, no. 1, pp. 18-37, Jan.-June 2010.
[9] H. Liu, H. Lieberman, and T. Selker, “A model of textual affect sensing using real-world knowledge” In Proceedings of the 8th international conference on Intelligent user interfaces, ACM, pp. 125-132, 2003.
[10] C. O. Alm , D. Roth , R. Sproat, “Emotions from text: machine learning for text-based emotion prediction”, In Proceedings of the conference on Human Language Technology and Empirical Methods in Natural Language Processing, pp. 579-586, British Columbia, Canada, Oct. 2005.
[11] S. Mohammad, “Portable features for classifying emotional text,” In Proceedings of the 2012 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies , Association for Computational Linguistics, pp. 587-591, Jun. 2012.
[12] S. Chaffar and D. Inkpen, “Using a heterogeneous dataset for emotion analysis in text,” In Advances in Artificial Intelligence, Springer Berlin Heidelberg, pp. 62-67, 2011.
[13] A. Bermingham, M. Conway, L. McInerney, N. O'Hare, and A. F. Smeaton, “Combining social network analysis and sentiment analysis to explore the potential for online radicalization,” In IEEE Social Network Analysis and Mining, 2009. ASONAM'09. International Conference on Advances in, pp. 231-236, Jul. 2009.
[14] C. Strapparava, M. Guerini, and O. Stock, “Predicting Persuasiveness in Political Discourses,” In LREC, 2010.
[15] I. Howley and T. Newman, “Factors impacting community response in an interest-sharing network,” In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, ACM, pp. 2283-2286, Apr. 2013.
[16] Chin Chih Yu. (2014.) DailyView [Online]. Available: http://dailyview.tw/
[17] A. Hassan, A. Abbasi, and D. Zeng, “Twitter Sentiment Analysis: A Bootstrap Ensemble Framework,” In IEEE Social Computing (SocialCom), 2013 International Conference on, pp. 357-364, Sep. 2013.
[18] R. Pfitzner, A. Garas, and F. Schweitzer, “Emotional Divergence Influences Information Spreading in Twitter,” in ICWSM, 12, 2-5. 2012.
[19] D. Quercia, “Don't worry, be happy: The geography of happiness on facebook,” In Proceedings of the 5th Annual ACM Web Science Conference, ACM, pp. 316-325, May. 2013.
[20] J. Kim and J. R. Lee, “Cyberpsychology, Behavior, and Social Networking,” pp. 359-364, Jun. 2011.
[21] E. Kross, et al., “Facebook use predicts declines in subjective well-being in young adults,” PloS one, vol. 8, no. 8, e69841. 2013.
[22] B. A. Feinstein, R. Herschenberg, V. Bhatia, J. A. Latack, N. Meuwly, and J. Davila, “Negative social comparison on Facebook and depressive symptoms: Rumination as a mechanism,” Psychology of Popular Media Culture, vol. 2, pp. 161-170, 2013.
[23] M. W. Newman, D. Lauterbach, S. A. Munson, P. Resnick, and M. E. Morris, “It's not that I don't have problems, I'm just not putting them on Facebook: challenges and opportunities in using online social networks for health,” In Proceedings of the ACM 2011 conference on Computer supported cooperative work, ACM, pp. 341-350, Mar. 2011.
[24] A. L. Hill, D. G. Rand, M. A. Nowak, and N. A. Christakis, “Emotions as infectious diseases in a large social network: the SISa model,” In Proceedings of the Royal Society B: Biological Sciences, rspb20101217. 2010.
[25] L. Coviello, Y. Sohn, A. D. Kramer, C. Marlow, M. Franceschetti, N. A. Christakis, and J. H. Fowler, “Detecting Emotional Contagion in Massive Social Networks,” PloS one, vol. 9, no. 3, e90315. 2014.
[26] A. D. Kramer, J. E. Guillory, and J. T. Hancock, “Experimental evidence of massive-scale emotional contagion through social networks,” In Proceedings of the National Academy of Sciences, 201320040. 2014.
[27] J. N. Bailenson, A. C. Beall, J. Loomis, J. Blascovich, and M. Turk, “Transformed Social Interaction: Decoupling Representation from Behavior and Form in Collaborative Virtual Environments,” Presence: Teleoperators & Virtual Environments, vol. 13, no. 4, pp. 428-441, 2004.
[28] B. J. Fogg, “Persuasive technology: using computers to change what we think and do,” Ubiquity, 2002(ember), vol. 5, Dec. 2002.
[29] G. Liu, S. Choudhary, J. Zhang, and N. Magenenat-Thalmann, “Let’s keep in touch online: a Facebook aware virtual human interface,” The Visual Computer, vol. 29, no. 9, pp. 871-881, 2013.
[30] G. Mark, S. Iqbal, M. Czerwinski, and P. Johns, “Capturing the mood: Facebook and face-to-face encounters in the workplace,” In Proceedings of the 17th ACM conference on Computer supported cooperative work & social computing, ACM, pp. 1082-1094, Feb. 2014.
[31] W.-T. Luo, "I am not at all sad with sad movies: explore entertainment with appraisal theory ", in Journal of Chinese Communication Society, 2013.
[32] R. A. Thompson, “Emotional regulation: A theme in search of definition,” Monographs of the Society for Research in Child Development, vol. 59, pp. 25-52, 1994.
[33] S. F. Chen, "A Path Model Construction of ICU Nurses' Irrational Beliefs, Emotional Traits, Emotional Management, and Their Interpersonal Relationship", National Political University, Taiwan, 2007.
[34] J. J. Gross, “The emerging field of emotion regulation: An integrative review,” Review of General Psychology, vol. 2, pp. 271-299, 1998.
[35] A. Aldao, S. Nolen-Hoeksema, and S. Schweizer, “Emotion-regulation strategies across psychopathology: a meta-analytic review,” Clinical Psychology Review, vol. 30, 217e237. 2010.
[36] J. J. Gross, and O. P. John, “Individual differences in two emotion regulation processes: implications for affect, relationships, and well-being,” Journal of personality and social psychology, vol. 85, no. 2, pp. 348, 2003.
[37] B. Parkinson, P. Totterdell, R. B. Briner, and S. Reynolds, “Changing moods,” New York, Addison, Wesley, Longman, 1996.
[38] W.-Y. Ma and K.-J. Chen, "Introduction to CKIP Chinese word segmentation sys-tem for the first international Chinese Word Segmentation Bakeoff", Annual Meeting of the ACL, Proceedings of the second SIGHAN workshop on Chinese language processing, vol. 17, pp. 168-171, 2003.
[39] Y. Sun, C. Chen, C. Liu, C. Liu, and V. Soo, "中文短句之情緒分類 (Sentiment Classification of Short Chinese Sentences) [In Chinese]", In Proc. ROCLING, 2010.
[40] T.-F. Cheng, Y. Li, & H. Zhang (Eds.), “Effects of semantic transparency and morphological structure on the representation and recognition of Chinese disyllabic words", in Proceedings of the Joint Meeting of the Fourth International Conference on Chinese Linguistics and the Seventh North American Conference on Chinese Linguistics, vol. 2, pp. 326-343, University of Southern California. 1996.
[41] K. J. Chen, and S. H. Liu, “Word identification for Mandarin Chinese sentences,” In Proceedings of the 14th conference on Computational linguistics, Association for Computational Linguistics, vol. 1, pp. 101-107, Aug. 1992.
[42] 教育部辭典 [Online]. Available: http://www.edu.tw/files/site_content/m0001/pin/yu7.htm?open
[43] L.-W. Ku and H.-H. Chen (2007). “Mining Opinions from the Web: Beyond Relevance Retrieval.” Journal of American Society for Information Science and Technology, Special Issue on Mining Web Resources for Enhancing Information Retrieval, 58(12), pages 1838-1850. Software [Online]. Available: http://nlg18.csie.ntu.edu.tw:8080/opinion/index.html
[44] Z. D. Dong and Q. Dong."Chinese/English Vocabulary for Sentiment Analysis (VSA)(Beta version)" HowNet. [Online]. Available: http://www.keenage.com
[45] A. Neviarouskaya, A. Masaki, "Sentiment Word Relations with Affect, Judgment, and Appreciation," IEEE Transactions on Affective Computing, vol. 4, pp. 425-438, Dec. 2013.
[46] R. E. Petty, and J. T. Cacioppo, “Communication and persuasion: Central and peripheral routes to attitude change,” Springer-Verlag, New York, NY, USA, 1986.
[47] LIBSVM: A Library for Support Vector Machines, C.-C. Chang and C.-J. Lin. (2001). [Online]. Available: http://www.csie.ntu. edu.tw/~cjlin/libsvm
[48] E. Cambria, A. Livingstone, and A. Hussain, “The hourglass of emotions,” In Cognitive behavioural systems, pp. 144-157, Springer Berlin Heidelberg, 2012.
[49] W. Lin, T. Wilson, J. Wiebe, A. Hauptmann, “Which side are you on? Identifying perspectives at the document and sentence levels,” In Conference on Natural Language Learning, pp. 109–116, 2006.
[50] S. D’Mello, S. Craig, J. Sullins, and A. Graesser, “Predicting affective states expressed through an emote-aloud procedure from autotutor’s mixed-initiative dialogue,” Int’l J. Artificial Intelligence in Education, vol. 16, pp. 3–28, 2006.
[51] S. D’Mello, N. Dowell, A. Graesser, ”Cohesion relationships in tutorial dialogue as predictors of affective states,” In Proceedings of Conf. Artificial Intelligence in Education, pp. 9–16, 2009.
[52] T. Danisman, A. Alpkocak, “Feeler: Emotion classification of text using vector space model,” In AISB, 2008.
[53] C. Strapparava, R. Mihalcea, “Learning to identify emotions in text,” In ACM Symp. Applied Computing, pp. 1556–1560, 2008.
[54] M. Grassi, E. Cambria, A. Hussain, F. Piazza, “Sentic web: A new paradigm for managing social media affective information,” Cognitive Computation, vol. 3, no. 3, pp. 480–489, 2011.
[55] B. Latané, “The psychology of social impact,” American Psychologist, vol. 36, pp. 343-356, 1981.
[56] E. Diener, R. Emmons, J. Larsen, and S. Griffin, “The Satisfaction With Life Scale,” Journal of Personality Assessment, vol. 49, pp. 71-75, 1985.
[57] D. Watson, L. A. Clark, and A. Tellegen, “Development and validation of brief measures of positive and negative affect: the PANAS scales,” Journal of personality and social psychology, vol. 54, no. 6, pp. 1063, 1988.
[58] S. Lyubomirsky and H. Lepper, “A measure of subjective happiness: Preliminary reliability and construct validation,” Social Indicators Research, vol. 46, pp. 137-155, 1999.
[59] I. T. U. T. Rec, “Methods for subjective determination of transmission quality,” International Telecommunication Union, Geneva, pp. 800, Aug. 1996.
[60] W. J. Gingerich, S. Eisengart, “Solution-focused brief therapy: a review of the outcome research,” Fam Process, vol. 39, pp. 477-498, 2000.
[61] S. Shazer, “Clues: Investigating Solutions in Brief Therapy,” New York, WW, Norton, 1988.
[62] R. A. Emmons, and A. Mishra, “Why gratitude enhances well-being: What we know, what we need to know,” Designing positive psychology: Taking stock and moving forward, pp. 248-262, 2011.
[63] O. F.Cabane, “The Charisma Myth: How Anyone Can Master the Art and Science of Personal Magnetism,” Penguin, 2012.
論文全文使用權限
  • 同意授權校內瀏覽/列印電子全文服務,於2019-08-29起公開。
  • 同意授權校外瀏覽/列印電子全文服務,於2019-08-29起公開。


  • 如您有疑問,請聯絡圖書館
    聯絡電話:(06)2757575#65773
    聯絡E-mail:etds@email.ncku.edu.tw