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研究生:王鶴偉
研究生(外文):Ho-Wei Wang
論文名稱:健康照護研究的新視野:運用網路搜尋與社群媒體探索肥胖照護議題
論文名稱(外文):A New Dimension of Health Care: the Uses of Google Trends and Social Media for Obesity Communication
指導教授:陳端容陳端容引用關係陳雅美陳雅美引用關係
指導教授(外文):Duan-Rung ChenYa-Mei Chen
口試日期:2017-07-13
學位類別:博士
校院名稱:國立臺灣大學
系所名稱:健康政策與管理研究所
學門:醫藥衛生學門
學類:公共衛生學類
論文種類:學術論文
論文出版年:2017
畢業學年度:105
語文別:英文
論文頁數:112
中文關鍵詞:搜尋引擎大數據社群媒體內容分析肥胖減重手術Google Trends
外文關鍵詞:Google TrendsInternet searchBig dataObesitySocial media
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Background: Despite the fact that many efforts and resources to prevent obesity were invested tremendously before, the obesity rate has continued to rise in Taiwan from 37.48% (2008) to 40.12% (2013). Therefore, a new direction of research becomes more critical. Nowadays, Internet has become a popular media for people searching for health-related knowledge and allows millions of users around the world to communicate through interactive network-oriented social media. The Internet world offers a new perspective for public heath to approach.
Objective: This study aims to investigate how Internet health search, online news media and social media affect the virtual obesity community on the Internet. I first explore the association between the business cycle and obesity-related search behavior on the Internet, and then followed by the investigation of the network of Facebook obesity community. Last, the content analysis of bariatric surgery on news media and social media is examined.
Material and method: Internet search data was downloaded from Google Trends. Social media data was crawled by Facebook API and Python crawling robot. SPSS statistics, ver 20.0 was used to calculate Pearson correlation coefficient. The UCINET 6.0 and NetDraw software were used to draw and analyze the network dataset.
Results: During pre-financial and financial crisis period, Taiwan stock index (TWSE) is positive associated with obesity-related awareness and behavior search, suggesting economic hardship may be the underlying force affecting individual obesity-related internet search. Facebook obesity community possessed network structure and small-world property, and the network clustering co-efficient changed over time. Individual choice, particularly eating, was mostly portrayed in obesity news. However, obesity stigmatization and discrimination were unfortunately filled in the news and reader’s comments.
Discussion: From public health viewpoints, Internet surveillance may offer a new way to prevent the obesity. Government may adopt an aggressive way to push effective obesity-related information to Internet through media or search engine. In addition, better management of virtual community on social media may lead to an efficient way to diffuse the correct obesity-related information.
Acknowledgements ……………………………………………………………………...I
Abstract (Chinese) ……………………………………………………………………...II
Abstract (English) ……………………………………………………………………...III
Table of Contents ……………………………………………………………………….V
List of Figures…………………………………………….……...…………………...XIII
List of Tables …..……………………………….....………………..………………….IX

Chapter 1 Introduction 1
1.1 Background 1
1.2 Purpose of the research 4
1.3 Research objectives 9
1.4 Significance of the research 11
Chapter 2 Literature review 13
2.1. Obesity 13
2.1.1 Obesity and prevalence 13
2.1.2 Obesity therapies 15
2.2 Health seeking behavior on the Internet 15
2.2.1 People’s information seeking behavior 15
2.2.2 Internet online health search 17
2.2.3 Online search strategies and collective behavior 20
2.3 Framework of the literature review 22
Chapter 3 Methodology 23
Chapter 4 Study 1 24
4.1 Literature review 24
4.1.1 Obesity and economy 24
4.1.2 Healthy behavior and the economy 26
4.1.3 Infodemiology research 29
4.1.4 The economy and Internet search strategy 34
4.2 Methods 38
4.2.1 Data Sources 38
4.3 Results 43
4.4 Discussion 51
Chapter 5 Study 2 57
5.1 Literature review 57
5.1.1 Social media and social network 57
5.1.2 Social media and health 59
5.1.3 Facebook fan page and likes 62
5.1.4 Small world 63
5.2 Methods 64
5.2.1 Data collection and web crawling 65
5.2.2 Network data processing and visualization 67
5.3 Results 69
5.4 Discussion 77
Chapter 6 Study 3 80
6.1 Literature review 80
6.1.1 Media content analysis 80
6.1.2 Stigma and discrimination 81
6.2 Methods 81
6.2.1 News media framing 81
6.2.2 Keywords presented most in bariatric surgery news 82
6.2.3 Obesity stigma in reader’s comments 83
6.3 Results 84
6.3.1 Media framing 84
6.3.2 Co-word analysis 86
6.3.3 Word cloud analysis 88
6.4 Discussion 91
Chapter 7 Conclusion 94
Chapter 8 Limitation 97
Reference 98

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