研究生: |
嚴慧晴 Yen, Hui-Ching |
---|---|
論文名稱: |
運用大數據與GPT-3語言模型探究社會知覺下候選人之網路新聞報導與社群輿論分析—以2022年女性候選人為例 Using Big Data and GPT-3 to Explore Candidates’Online News and Public Opinion in Social Perception:A Case Study of 2022 Female Candidates |
指導教授: |
蔣旭政
Chiang, Hsu-Cheng |
口試委員: |
蔣旭政
Chiang, Hsu-Cheng 賴玉釵 Lai, Yu-Chai 陳慧蓉 Chen, Huey-Rong |
口試日期: | 2024/03/28 |
學位類別: |
碩士 Master |
系所名稱: |
大眾傳播研究所 Graduate Institute of Mass Communication |
論文出版年: | 2024 |
畢業學年度: | 112 |
語文別: | 中文 |
論文頁數: | 103 |
中文關鍵詞: | 大數據 、GPT-3 、女性候選人 、社會感知 、網路新聞 、社群輿論 |
英文關鍵詞: | big data, GPT-3, female candidates, social perception, online news, public opinion |
研究方法: | 大數據分析取徑 、 GPT-3語言模型 |
DOI URL: | http://doi.org/10.6345/NTNU202400457 |
論文種類: | 學術論文 |
相關次數: | 點閱:167 下載:20 |
分享至: |
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在2022年九合一選舉中,台灣地方首長女性參選人數創下台灣30年來最高紀錄,於同年,各黨開始出現眾多正妹候選人參選現象,引起新聞媒體與社群媒體熱烈討論。因此,本研究將研究問題分為網路新聞、社群媒體兩個面向作探討。首先,探討網路新聞面向:在《聯合新聞網》、《自由時報電子報》 、《中時新聞網》 傳統三大報網路新聞媒體中,針對「2022女性里長候選人」相關之新聞主要關注面向為何?其次,探討社群媒體面向:在社群媒體PTT中,針對「2022女性候選人」相關之文章主要關注面向為何?將透過大數據分析取徑、詞頻分析與文字雲,對文本進行分析。最後,針對「2022女性候選人」相關文章下的留言來探討是否存在政治娛樂化現象?輔以GPT-3語言模型將PTT之留言分類為「政治娛樂化」、「非政治娛樂化」、「與選舉無關」三種類目。
研究結果顯示,研究問題一結果:針對「2022女性里長候選人」之詞頻分析發現,三間網路新聞皆出現最美、正妹、美女詞彙,出現物化女性、將女性幼體化現象,也發現《自由時報電子報》較其他兩大報更娛樂化。研究問題二結果:針對「2022女性候選人」之PTT文章詞頻分析發現,「民進黨」與「國民黨」兩大黨為網民最關注的面向,而「柯文哲」一詞在PTT文章及留言為高頻率詞彙,發現PTT存有網軍現象。而從「2022女性候選人姓名」討論詞頻中也發現社群討論頻率與得票數不一定相關。研究問題三結果:PTT留言存在政治娛樂化現象,包含歧視女性候選人之外表、以其姓名作諧音嘲諷,及出現諷刺民進黨支持者等貶義詞,顯示網路的匿名性特質出現態度極化的攻擊性言論與社群媒體之厭女言論現象。
In the 2022 nine-in-one election, the number of female candidates for local cacique in Taiwan set a record for Taiwan in 30 years. In the same year, various political parties have many pretty girls participating in the election, which caused heated discussions in the news media and social platforms. Therefore, this study divides the research questions into two aspects: online news and social media. First, explore the aspects of online news. In "udn.com", "ltn.com", "chinatimes.com" What are the main concerns of the three traditional online news media of the three major newspapers in their reports on "2022 female village chief candidates"? Secondly, discuss the orientation of social media: In PTT, what are the main focuses of articles related to "2022 female candidates"? Explore the text through big data analysis, word frequency analysis and word cloud. Finally, let’s explore whether the comments on articles related to “2022 Female Candidates” are politically entertaining? The research also use GPT-3 to classify PTT comment into three categories: "political entertainment", "non-political entertainment", and "not related to elections".
Results of Research Question 1:The word frequency analysis of "2022 female village chief candidate" found that the words "most beautiful", "hot girls" and "beautiful girls" appeared in the three online news, which appeared to objectify women and infantilize women.Among the three major newspapers, it was also found that "ltn.com" contained more entertainment-oriented words than the other two major newspapers.
Results of Research Question 2:Word frequency analysis of PTT articles on "2022 Female Candidates" found that the two major parties, DPP and KMT, were discussed most frequently by netizens, and "Ko Wen-je" is a high-frequency word in PTT articles and comments, and it is found that have cyber warrior on the PTT forum. "2022 Female Candidate Names" also is a high-frequency word, that found social opinion is not necessarily related to votes.
Results of Research Question 3: There are political entertainment phenomena in PTT comments, including discriminating against the appearance of female candidates, mocking their names with homophonic names, using derogatory terms to satirize DPP supporters, etc., which highlights the anonymity of the Internet and the popularity of social media platforms. There is widespread offensive rhetoric and misogynistic rhetoric.
一、中文文獻
BBC,〈台灣選舉:台北市長柯文哲求連任 藍綠夾攻下夾縫生存。〉,https://www.bbc.com/zhongwen/trad/chinese-news-46271378,搜尋日期:2018年11月20日
LINE TODAY(2022 年 10 月 07 日) 。徐巧芯「粗俗三字」酸陳吉仲遭截圖瘋傳 律師開轟:極度羞辱。https://today.line.me/tw/v2/article/EXv6oBk。搜尋日期: 2024 年 04 月 08 日
Hamermesh,Daniel著,陳正芬譯,2011,《美麗有價》,時報文化。
LIFE 生活網(2022 年 12 月 07 日)。爆乳議員2/專家:Molly翎熹靠空戰當選 南市林依婷用網路擠走老將。https://m.life.tw/?app=view&no=1801017 搜尋日期: 2023 年 10 月 18 日
Newtalk新聞。〈 網軍價目表流出?柯粉嗨喊抓到綠營1450 四叉貓Po原圖:柯文哲的〉。https://reurl.cc/13EM7m。搜尋日期:2024 年 3 月 1 日
三立新聞網(2022 年 11 月 21 日)。為什麼「正妹候選人」越來越多? 她點1歪風狂嘆:國之將亡。https://www.setn.com/News.aspx?NewsID=1211523搜尋日期: 2023 年 10 月 18 日。
女人迷,〈【性別觀察】誰是母豬教徒?當仇女成為一種流行〉,https://womany.net/read/article/10857, 2016年6月6日
中天新聞網,〈民進黨稱「資料太多」交不出性騷報告!網友狂刷「這句」迷因太地獄〉,https://reurl.cc/rro2lN,2023年06月05日
中央社(2021年7月26日)。PTT解禁全面開放註冊 新增手機認證。https://www.cna.com.tw/news/firstnews/202107260059.aspx 搜尋日期: 2023 年 10 月 18 日。
中央社(2022)。2022九合一選舉。https://www.cna.com.tw/project/20221024-women-in-election/ 搜尋日期: 2023 年 10 月 18 日。
中央社,〈縣市長候選人女力創新高 細看30年來女選將如何煉成〉,https://www.cna.com.tw/project/20221024-women-in-election/,2022年
中央廣播電台。〈 范雲公布政治人物厭女等十大類型 呼籲全民下架退步政黨及政治人物 〉。https://www.rti.org.tw/news/view/id/2187559。搜尋日期:2024 年 3 月 1 日
今日新聞。〈 開箱網軍5/藍綠側翼粉絲團大比拚 都靠梗圖炒熱議題 〉。https://reurl.cc/4jOvlD。搜尋日期:2024 年 3 月 1 日
內政部政黨資訊網,2022,〈 政 黨 專 區 簡 介 〉 ,https://party.moi.gov.tw/politics/party!list.action,查閱時間:2023/02/15。
天下雜誌。〈 一個PTT重度使用者的新聞幕後:八卦板變得愈來愈怪 〉。https://www.cw.com.tw/article/5094900。搜尋日期:2024 年 3 月 1 日
王泰俐(2013)。「臉書選舉」? 2012 年台灣總統大選社群媒體對政治參與行為的影響。東吳政治學刊。31(1):1-52。
王貿(2020)。公務人員關注議題之文字探勘: 以 PTT 公職板為例。調查研究-方法與應用,45,119-154。
王嵩音,〈社交媒體政治性使用行為與公民參與之研究〉,《資訊社會研究》,第 32 期,2017 年 1 月,頁 83-112。
左宗宏、李俊憲,2010,〈台灣報紙選舉新聞偏差報導現象研究-2000 與 2004 年總統大選的比較分析〉,《傳播與社會學刊》,11:141-163。
民視新聞網。〈全民筆讚 翁達瑞-什麼是側翼網軍?〉https://www.ftvnews.com.tw/news/detail/2022B30W0071 。搜尋日期:2024 年 3 月 1 日
伊任(2020)。〈2020 總統大選網路輿情分析-以KEYPO大數據關鍵引擎為分析工具〉。銘傳大學新媒體暨傳播管理學系碩士在職專班碩士論文。
自由時報電子報(2018年11月19日)。網選全台10大正妹候選人 蔡宜芳濁水溪以南唯一入圍者https://news.ltn.com.tw/news/politics/breakingnews/2617362搜尋日期: 2023 年 10 月 18 日。
自由時報電子報(2018年11月25日)。全國「10大正妹議員候選人」 這「7人」凍蒜! https://news.ltn.com.tw/news/politics/breakingnews/2623706搜尋日期: 2023 年 10 月 18 日。
吳乃德,1993,國家認同與政黨支持,中央研究院民族學研究所集刊 74: 33-61.
吳君孝, 李蔡彥, 鄭宇君, & 陳百齡. (2014). 社群感測器: 社群媒體分析工具之設計 (Doctoral dissertation, 吳君孝).
吳紫瑀(2023)。《 政治、科技與兩岸關係:2016-2022傳播「政策」報導與評論之分析》 。國立政治大學碩士論文。
周刊王CTWANT。〈 民進黨輸到脫褲!綠營內部揪「5 大戰犯」:網軍治國惹人厭〉。 https://reurl.cc/A4abv3 。搜尋日期:2024 年 3 月 1 日
周桐(2017),《哈姆雷特》:時代背景下的"厭女症"傾向,《安徽文學》,08: 39-40。
林東泰(1997)。《大眾傳播理論》。台北市:師大書苑。
林思平(2017)網路八卦與真理政治: 批踢踢八卦板之閱聽人研究. 新聞學研究, (133), 135-188.
林淑芳(2018)。社群媒體與政治公民參與:網路政治討論頻率與政治討論異質性的中介角色。傳播與社會學刊,(44),25-48。https://doi.org/10.30180/CS.201804_(44).0003
施琮仁(2017)。〈台灣青少年網路霸凌現況、原因與影響〉。《中華傳播學刊》,32,203-240。
洪貞玲、廖雅琴、林舫如(2008)。〈國際新聞的國內化和小報化:以我國報紙報導 WTO 香港會議為例〉。《中華傳播學刊》,14,77-114。
胡竣賓、林柏青. (2019, November). PTT 用戶行為之分析與探討. In NCS 2019 全國計算機會議 (pp. 179-183). 國立金門大學.
唐士哲,2014a,〈從政治化媒介到媒介化政治:電視政論節目作為制度化的政治實踐〉,《中華傳播學刊》,25:3-43。
翁秀琪、孫秀蕙(1995). 〈性別政治?從民國八十二年台灣地區縣、市長選舉看性別、傳 播與政治行為〉,《新聞學研究》,第五十一集,頁 87-111。
張玉佩、葉孟儒(2008)。〈美貌的詛咒:男性凝視在網路相簿的權力探索〉。《資訊社會研究》,15:249-274。
張春興(1991)。張氏心理學辭典。台北:東華書局
張致瑜(2014)。《應用文字雲技術分析四大平面媒體與社群網站關注議 題之差異:以洪仲丘事件為例》。銘傳大學傳播管理學系碩士在職專班論文。
張悅倫(2022)。《文字生成技術應用於學術論文寫作之評估─以人工智慧領域論文摘要為例》。國立臺灣師範大學圖書資訊學研究所。
張儀同(2022)。深度偽造政治廣告之外表吸引力、性別與公共政策類型對候選 人評價、形象及投票意願影響:以臺灣年輕選民為例。國立臺灣師範大學 大眾傳播研究所碩士論文,臺北市。
莊伯仲(2000)。網路選戰在台灣-1998年三合一大選個案研究。廣告學研究,14,31-52。
莊伯仲、鄭自隆(1995)。競選文宣新媒介﹣台灣政治性資訊網路現況研究。《廣告學研究》,第7集,頁99。
郭繐慈(2022)。臺灣政治人物的政治社群行銷: 以 2020 總統大選臉書粉絲專頁內容分析為例.
陳怡姗(2023)。《政治候選人的議題及特質所有權的跨媒體議題設定:以2020年台灣總統大選為例》。國立中山大學行銷傳播管理研究所論文
陳建丞(2005)。應徵者外表吸引力對面試官評量效應之影響-以面試官訓練為干擾變數。人力資源管理學報,5(4),55-66
報導者。〈葉浩/第一位「女」總統的想像〉。 https://www.twreporter.org/a/opinion-female-president,2016年1月17日
報導者。〈網路聲量=實際選票?24張圖解密六都市長的網路聲量戰爭〉,https://www.twreporter.org/i/2018-election-report-sharevoice-gcs,2018年11月24
彭芸(2001)。《新媒介與政治——理論與實證》。台北:五南。
曾昭媛(2019年12月18日)。〈婦女新知基金會【投書】請停止性別歧視,回歸政策辯論〉。婦女新知基金會。https://www.awakening.org.tw/news/5353
華視全球資訊網(2022年8月14日)。比能力拚顏值 美女參選人征戰年底大選。https://news.cts.com.tw/cts/general/202208/202208142088869.html搜尋日期: 2023 年 10 月 18 日。
馮奕達(譯)(2021)。顏值:從第一印象到刻板印象,臉孔社交價值的科學解密(原作者:Alexander Todorov)。臺北市:鷹出版。(原著出版年:2017)。
黃彥超,《社群媒體行銷與消費者信任關係之研究-以 FACEBOOK 為例》(臺北:中國文化大學商學 院國際企業管理學系/碩士論文,2013 年),頁 7-59。
黃順星(2010)。〈新聞的場域分析:戰後台灣報業的變遷〉,《新聞學研究》,104:113-160。
微軟新聞中心(2022)。微軟新推出Azure OpenAI 服務,結合GPT-3 語言模型與 Azure 企業功能。https://news.microsoft.com/zh-tw/features/azure-openai/。搜尋日期: 2023 年 10 月 18 日。
新新聞。〈誰是黑手2》網軍與他們的產地PTT假帳號、臉書粉專言論無法管 〉。https://new7.storm.mg/article/4486250。搜尋日期:2024 年 3 月 1 日
楊婉瑩,2019,〈沒有選擇的選擇──女性從政者的雙重束縛〉,《這是愛女,也是厭女:如何看穿這世界拉攏與懲戒女人的兩手策略?》,王曉丹主編,大家出版:172-193。
管婺媛(2018 年 11 月 25 日)。〈北柯P南國瑜》網紅市長稱霸北高 政治新浪潮來襲〉。《商周》。https://www.businessweekly.com.tw/focus/blog/25336搜尋日期: 2023 年 10 月 18 日。
銘報(2023年11月22日)。林啟耀:大數據結合社會科學 快速掌握輿情。https://reurl.cc/XqpgZj。搜尋日期: 2023 年 11 月 28 日。
劉昌德(2020)。〈小編新聞學:社群媒體與通訊軟體如何轉化新聞專業〉。《新聞學研究》,142,1-58。
劉秋月(2011)。《資訊科技媒介應用在政治選舉之行銷效果:以2010五都選舉為例》。中華大學資訊管理學系碩士論文。
劉振隆, 郭庭瑜, 黃湋宸, & 蔡佳潔. (2018). 以社群大數據基礎之台灣民眾國外旅遊概況與觀光行為模式. 觀光與休閒管理期刊, 6, 13-22.
劉嘉薇(2017)。網路統獨的聲量研究:大數據的分析。政治科學論叢,(71),113-165。
https://doi.org/10.6166/TJPS.71(113-166)
數位時代(2018年11月09日)。讚數多等於選票多嗎?YouTuber呱吉這樣闖政壇。 https://www.bnext.com.tw/article/51200/froggy-chiu-youtuber-election搜尋日期: 2023 年 10 月 18 日。
蔡依霖. (2016). 以鉅量資料取徑分析 facebook 候選人網路競選行為及群眾討論行為—2014 台北市長選舉個案研究.
蔡承志譯,Neil Postman 原著,2016,《娛樂至死:追求表象、歡笑和 激情的媒體時代》(二版),臺北市:貓頭鷹出版。
鄭宇君,〈社交媒體假訊息的操作模式初探:以兩個臺灣政治傳播個案為例〉,《中華傳播學刊》, 第 39 期,2021 年 6 月,頁 3-41。
鄭宇君、陳百齡(2014)。〈探索 2012 年台灣總統大選之社交媒體浮現社群:巨量資料分析取徑〉。《新聞學研究》,120,121-165。
盧沛樺、張玉佩(2010)。〈性別差異政治:女性運動員的媒體再現與認同糾葛〉。《中華傳播學刊》,17:139-170。
盧孟宗(2014),「第三章「權力、決策與影響力」案例分析」,載於行政院性別平等處(主 編),《識讀性別平等與案例分析》(45-55 頁)。臺北市:行政院。
聯合新聞網。〈網軍加班大動作!PTT創設人杜奕瑾:已抓包近200網軍帳號 〉。https://udn.com/news/story/120912/6512780。搜尋日期:2024 年3月1 日
謝幸霖 ( 2010 )。《數位時代下假訊息對民主的影響及其管制》。東吳大學法學院法律學系碩士在職專班法律專業組碩士論文。
關鍵評論網(2021年05月04日)。政治人物的網路小編:是專業幕僚,還是裹糖衣的包裝師? https://www.inside.com.tw/article/23391-politicians-web-editor搜尋日期: 2023 年 10 月 18 日。
關鍵評論網,2023,〈雖然總統一直是藍綠輪流當,但我認為台灣並不存在「兩黨制」 〉,https://www.thenewslens.com/article/186920/page2 查閱時間:2023/02/15。
二、英文文獻
Altheide, D. L., & Snow, R. P. (1979). Media logic. Beverly Hill, CA: Sage.
Archenaa, J., & Anita, E. M. (2015). A survey of big data analytics in healthcare and government. Procedia Computer Science, 50, 408-413.
Baker, S., & White, K. M. (2010). In their own words: Why bloggers blog anonymously. CyberPsychology, Behavior, and Social Networking, 13(6), 619-624.
Bennett, W. L., & Segerberg, A. (2012). The logic of connective action: Digital media and the personalization of contentious politics. Information,Communication & Society, 15(5), 739-768.
Berggren, N., Jordahl, H., & Poutvaara, P. (2007). The looks of a winner: Beauty, gender, and electoral success.
Boyd, D. M., & Ellison, N. B. (2007). Social network sites: Definition, history, and scholarship. Journal of computer‐mediated Communication, 13(1), 210-230.
Bradshaw, S., & Howard, P. (2017). Troops, Trolls and Troublemakers: A Global Inventory of Organized Social Media Manipulation. In Computational Propaganda Research Project (pp. 1–37). Oxford Internet Institute.
Bystrom, D., Robertson, T. A., & Banwart, M. C. (2001). Framing the fight: An analysis of media coverage of female and male candidates in primary races for governor. American Behavioral Scientist, 44(12), 1999-2013.
Caballero, M. J., & Pride, W. M. (1984). Selected effects of salesperson sex and attractiveness in direct mail advertisements. Journal of Marketing, 48(1), 94-100.
Campbell, A., Converse, P. E., Miller, W. E., & Stokes, D. E. (1960). The American Voter. Chicago: The University of Chicago Press.
Chen, M., Mao, S., & Liu, Y. (2014). Big data: A survey. Mobile Networks and Applications, 19(2), 171-209.
Chiu, K. L., Collins, A., & Alexander, R. (2021). Detecting hate speech with gpt-3. arXiv preprint arXiv:2103.12407.
Clarke, I. & Grieve, J. (2017). Dimensions of Abusive Language on Twitter. Proceedings of the First Workshop on Abusive Language Online, pp. 1-10. DOI: 0.18653/v1/W17-3001.
Cocker, H. L., & Cronin, J. (2017). Charismatic authority and the YouTuber: Unpacking the new cults of personality. Marketing Theory, 17(4), 455–472.
Coe, K., Kenski, K., & Rains, S. A. (2014). Online and uncivil? Patterns and determinants of incivility in newspaper website comments. Journal of Communication, 64, 658-679。
Cohen, J. (1960). A coefficient of agreement for nomial scales. Educational and Psychological Measurement, 20, 37-46.
DataReportal(2022).Digital 2022: Global Overview Report. https://datareportal.com/reports/digital-2022-global-overview-report
Delli Carpini, M. X. (2000). Gen.com: youth, civic engagement, and the new information environment. Political Communication, 17, 341–349.
Dery, M. (Ed.). (1994). Flame wars: the discourse of cyberculture. Duke University Press.
Ding, P. (2019, August). Application of Big Data in Sports Science and Reflections. In Journal of Physics: Conference Series (Vol. 1302, No. 4, p. 042048). IOP Publishing.
Dion, K., Berscheid, E., & Walster, E. (1972). What is beautiful is good. Journal of personality and social psychology, 24(3), 285.
Fisher, D. R. (2012). Youth political participation: Bridging activism and electoral politics. Annual Review of Sociology, 38, 119–137.
Fredrickson B., Roberts T. (1997). Objectification theory: Toward understanding women’s lived experiences and mental health risks. Psychology of Women Quarterly, 21, 173–206. doi:10.1111/j.1471-6402.1997.tb00108.x
Fridkin, K. L., & Kenney, P. J. (2011). The role of candidate traits in campaigns. TheJournal of Politics, 73(1), 61-73.
Ghani, N. A., Hamid, S., Hashem, I. A. T., & Ahmed, E. (2019). Social media big data analytics: A survey. Computers in Human Behavior, 101, 417-428.
Gibson, R., & Cantijoch, M. (2013). Conceptualizing and measuring participation in the age of the internet: Is online political engagement really different to offline?. The Journal of Politics, 75(3), 701-716.
Gil de Zúñiga, H., Jung, N., & Valenzuela, S. (2012). Social media use for news and individuals' social capital, civic engagement and political participation. Journal of computer-mediated communication, 17(3), 319-336.
Goffman, E. (1949). The presentation of self in everyday life. American Journal of Sociology, 55, 6-7.
Graber, D. A. (1972). Personal qualities in presidential images: The contribution of the press. Midwest Journal of Political Science, 16, 46-76.
Grover, P., & Kar, A. K. (2017). Big data analytics: A review on theoretical contributions and tools used in literature. Global Journal of Flexible Systems Management, 18, 203-229.
Hatfield, E., & Sprecher, S. (1986). Mirror, mirror: the importance of looks in everyday life, Albany, N.Y. State University of New York.
Hayes, D. (2005). Candidate qualities through a partisan lens: A theory of trait ownership. American Journal of Political Science, 49(4), 908-923.
Heflick N., Goldenberg J., Cooper D., Puvia E. (2011). From women to objects: Appearance focus, target gender, and perceptions of warmth, morality and competence. Journal of Experimental Social Psychology, 47, 572–581. doi:10.1016/j.jesp.2010.12.020
Jayaraman, P. (2017). Internet of things (IoT) based big data analysis for agriculture monitoring and applications. Journal of King Saud University-Computer and Information Sciences.
Jayaraman, P. P., Yavari, A., Georgakopoulos, D., Morshed, A., & Zaslavsky, A. (2016). Internet of things platform for smart farming: Experiences and lessons learnt. Sensors, 16(11), 1884.
Johnson, T. J. & Kaye, B. K. (2003). A boost or bust for democracy? How the web influenced political attitudes and behaviors in the 1996 and 2000 presidential elections. Press/Politics, 8(3), 9-34.
Joinson, A. N., & Paine, C. B. (2007). Self-disclosure, privacy and the Internet. In A. N. Joinson, K. Y. A. McKenna, T. Postmes, & U. D. Reips (Eds.), The Oxford Handbook of Internet Psychology (pp. 237-252). Oxford University Press.
Kahn, Kim Fridkin(1994a). “Does Gender Make a Difference? An Experimental Examination of Sex Stereotypes and Press Patterns in Statewide Campaigns.” American Journal of Political science, 38: 1, pp.162-195.
Kahn, Kim Fridkin(1994b).”The Distorted Mirror: Press Coverage of Women Candidates for Statewide Office.” The Journal of Politics 56:1, pp.154-173.
Kavanagh, E., Litchfield, C., & Osborne, J. (2019). Sporting women and social media: Sexualization, misogyny, and gender-based violence in online spaces. International Journal of Sport Communication, 12(4), 552-572.
Kennedy, G. (2022). The Evolution of Russian Electoral Interference: 2016 and 2020 US Presidential Elections (Doctoral dissertation).
Kim, W. G., Han, J. S., & Lee, E. (2001). Effects of relationship marketing on repeat purchase and word of mouth. Journal of Hospitality & Tourism Research, 25(3), 272-288.
Kim, Y. M. (2015). The convergence of politics and entertainment: The politics of personal concern. Content is King: News management in the digital age/Ed. by G. Graham, A. Greenhill, D. Shaw, CJ Vargo, 53-69.
Kim, Y., & Khang, H. (2014). Revisiting civic voluntarism predictors of college students’ political participation in the context of social media. Computers in Human Behavior, 36, 114–121.
Kushin, M. J., & Yamamoto, M. (2013). Did social media really matter? College students' use of online media and political decision making in the 2008 election. In New Media, Campaigning and the 2008 Facebook Election (pp. 55-78). Routledge.
Kushwaha, A. K., Kumar, P., & Kar, A. K. (2021). What impacts customer experience for B2B enterprises on using AI-enabled chatbots? Insights from Big data analytics. Industrial Marketing Management, 98, 207-221.
LAGERKVIST*, J. O. H. A. N. (2008). Internet ideotainment in the PRC: National responses to cultural globalization. Journal of Contemporary China, 17(54), 121-140.
Laney, D. (2001). 3D data management: Controlling data volume, velocity and variety. META group research note, 6(70), 1.
Li, S. (2017). Rational Thinking on the Application of Artificial Intelligence in Sports. Journal of Nanjing Institute of Physical Education (Social Sciences), 31(5), 98-101.
Machiavelli, N. The Prince (New York: New American Library, 1952). Volume IV: What works, what matters, what lasts, 93.
Manovich, L. (2011). Trending: The promises and the challenges of big social data. Debates in the digital humanities, 2(1), 460-475.
McKenna, K. Y., & Bargh, J. A. (1998). Coming out in the age of the Internet: Identity" demarginalization" through virtual group participation. Journal of personality and social psychology, 75(3), 681.
Morgan, S. (2018). Fake news, disinformation, manipulation and online tactics to undermine democracy. Journal of Cyber Policy, 3(1), 39-43.Nielsen, R. K. (2012). Ground wars: Personalized communication in political campaigns: Princeton University Press.
Nielsen, R. K. (2012). Ground wars: Personalized communication in political campaigns: Princeton University Press.
Nisbett, R. E., & Wilson, T. D. (1977). Telling more than we can know: Verbal reports on mental processes. Psychological Review, 84(3), 231-259.
Olivola, C. Y., & Todorov, A. (2010). Elected in 100 milliseconds: Appearance-based trait inferences and voting. Journal of nonverbal behavior, 34, 83-110.
Olivola, C. Y., & Todorov, A. (2010). Fooled by first impressions? Reexamining the diagnostic value of appearance-based inferences. Journal of Experimental Social Psychology, 46(2), 315-324.
Pamela Turton-Turner, Villainous Avatars: The Visual Semiotics of Misogyny and Free Speech in Cyberspace, 2 (2018), http://forumonpublicpolicy.com/vol2013.no1/vol2013archive/turton.pdf (last visited Mar. 26, 2018).
Panagopoulos, C., Gueorguieva, V., Slotnick, A., Gulati, G., & Williams, C. (2009). Politicking online: The transformation of election campaign communications. Rutgers University Press.
Patzer, G. L. (1983). Source credibility as a function of communicator physical attractiveness. Journal of Business Research, 11, 229-241.
Petroshius, S. M., & Crocker, K. E. (1989). An empirical analysis of spoken person characteristics on advertisement and product evaluations. Journal of the Academy of Marketing Science, 41, 847-855.
Postmes, T., Spears, R., & Lea, M. (2000). The formation of group norms in computer-mediated communication. Human Communication Research, 26(3), 341-371.
Quintelier, E., & Vissers, S. (2008). The effect of Internet use on political participation: An analysis of survey results for 16-year-olds in Belgium. Social science computer review, 26(4), 411-427.
Rosar, U., Klein, M., & Beckers, T. (2008). The frog pond beauty contest: Physical attractiveness and electoral success of the constituency candidates at the North Rhine‐Westphalia state election of 2005. European Journal of Political Research, 47(1), 64-79.
Rosenberg, M. J., Hovland, C. I., McGuire, W. J., Abelson, R. P., & Brehm, J. W. (1960). Attitude organization and change: An analysis of consistency among attitude components.(Yales studies in attitude and communication.), Vol. III.
Rosenberg, S. W., & McCafferty, P. (1987). The Image and the Vote Manipulating Voters’ Preferences. Public Opinion Quarterly, 51(1), 31. https://doi.org/10.1086/269012
Rosenberg, Shawn W., Kahn, Shulamit & Tran, Thuy(1991).”Creating a Political Image: Shaping Appearance and manipulating the Vote.” Political Behavior 13:4, pp.345-367.
Rowe, I. (2015). Civility 2.0: A comparative analysis of incivility in online political discussion. Information, Communication & Society, 18(2), 121-138.
Safko, L. (2010). The social media bible: tactics, tools, and strategies for business success. John Wiley & Sons.
Satana, A. D. (2014). Virtuous or Vitriolic: The effect of anonymity on civility in online newspaper reader comment boards. Journalism Practice, 8(1), 18-33.
Scheller, M., Matorres, F., Little, A. C., Tompkins, L., & de Sousa, A. A. (2021). The role of vision in the emergence of mate preferences. Archives of Sexual Behavior, 1-13.
Schramm, W. (1949). The nature of news. Journalism Bulletin, 26(3), 259-269.
Simon Kemp(2023, February 13). DIGITAL 2023: TAIWAN. DataReportal – Global Digital Insights. https://datareportal.com/reports/digital-2023-taiwan
Sinanan, J. (2017). Social media in Trinidad: values and visibility (p. 250). UCL Press.
Sparks, C. (2000). Introduction: The panic over tabloid news. Tabloid tales: Global debates over media standards, 1-40.
Suler, J. (2004). The online disinhibition effect. CyberPsychology & Behavior, 7(3), 321-326.
Theocharis, Y., Barberá, P., Fazekas, Z., Popa, S. A., & Parnet, O. (2016). A bad workman blames his tweets: The consequences of citizens' uncivil Twitter use when interacting with party candidates. Journal of communication, 66(6), 1007-1031.
Tumasjan, A., Sprenger, T., Sandner, P., & Welpe, I. (2010, May). Predicting elections with twitter: What 140 characters reveal about political sentiment. In Proceedings of the international AAAI conference on web and social media (Vol. 4, No. 1, pp. 178-185).
Turton-Turner, P. (2013, March). Villainous avatars: the visual semiotics of misogyny and free speech in cyberspace. In Forum on Public Policy: A Journal of the Oxford Round Table. Forum on Public Policy.
Valenzuela, S., Park, N., & Kee, K. F. (2009). Is there social capital in a social network site?: Facebook use and college students’ life satisfaction, trust, and participation. Journal of Computer-Mediated Communication, 14(4), 875–901.
Vickery, J. R. (2018). This isn’t new: Gender, publics, and the internet. Mediating misogyny: Gender, technology, and harassment, 31-49.
Walther, J. B., & D'Addario, K. P. (2001). The impacts of emoticons on message interpretation in computer-mediated communication. Social Science Computer Review, 19(3), 324-347.
Wang, Y., Xiuping, S., & Zhang, Q. (2021). Can fintech improve the efficiency of commercial banks?—An analysis based on big data. Research in international business and finance, 55, 101338.
Zheng, M., Zhang, S., Zhang, Y., & Hu, B. (2021). Construct food safety traceability system for people’s health under the internet of things and big data. IEEE Access, 9, 70571-70583.
Zhu, L., Yu, F. R., Wang, Y., Ning, B., & Tang, T. (2018). Big data analytics in intelligent transportation systems: A survey. IEEE Transactions on Intelligent Transportation Systems, 20(1), 383-398.