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
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 
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 Active or passive 23 Friend interaction habits 24 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
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