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題名 結合大數據與厚數據方法觀察社群媒介上網紅對閱聽人的情緒渲染效果
Combining Big Data and Thick Data Methods to Analyze the Emotional Contagion Effect of Social Media Influencers on Audience作者 莊喬羽
Chuang, Chiao-Yu貢獻者 許志堅
Sheu, Jyh-Jian
莊喬羽
Chuang, Chiao-Yu關鍵詞 厚數據
大數據
情緒渲染
網紅
社群媒體
thick data
big data
emotional contagion
internet celebrity
social media日期 2023 上傳時間 2-八月-2023 14:09:21 (UTC+8) 摘要 2020年起，受到Covid-19疫情影響，人們進行遠端學習與線上互動的比率大幅提升。台灣民眾使用Youtube平台觀看影片的頻率上升，促進網路紅人（internet celebrity）職業的崛起。網紅進行更加多元化的創作，並快速累積粉絲數，甚至企業與品牌也會邀請網紅拍攝廣告或業配，顯示網紅對市場和民眾的影響力。然而，網紅除了帶動產業發展外，也會影響閱聽人的思想與行為，形成情緒渲染（emotional contagion）現象。在過去社群媒體的研究中，由於數位足跡（digital footprint）的建立，使大數據研究的資料蒐集更便利。然而，大數據簡化資料中的情感或故事，使研究者難以深入了解使用者脈絡。厚數據（thick data）透過增加資料厚度的方式，除了解決大數據無形中剔除資料中所包含的背景、故事或意義的問題，也能了解人的真實需求。本研究為分析網紅如何透過影音內容對閱聽人產生情緒渲染效果，以生活娛樂、業配行銷、知識資訊、時事與政治等台灣的四大類型網紅為主，結合大數據和厚數據研究方法增厚數位足跡資料，蒐集總計810部影片樣本資料，來建構影片類目並進行資料分析。經分析結果顯示，網紅可以透過影音內容的情緒表述影響閱聽人產生相似的情緒，且網紅在影片中所使用的新聞時事與政治議題行銷操作手法確實會影響閱聽人的正、負向情緒或態度。其中業配行銷、知識資訊、生活娛樂型網紅較常引起閱聽人的正向情緒，時事與政治型網紅的影片則較常引發閱聽人的負向情緒。不過，從時事與政治型網紅的影片樣本中，我們也發現當影片中的正向和負向情緒比例相近時，負向情緒的感染力更大。此外，在疫情內容主題取樣的影片中，我們觀察到網紅確實會受到重大事件的影響製作影片，並且在相同的影片題材中，網紅在影片中的情緒與態度會改變閱聽人的情緒或態度。
Due to Covid-19, Taiwanese have significantly increased the rate of remote learning and online interaction since 2020. Taiwanese users use Youtube more frequently to watch video contents, which has promoted the rise of the career of internet celebrities. Internet celebrities carry out more diversified creations and quickly accumulate fans. Even enterprises and brands will invite internet celebrities to film the advertisement or create advertorials, showing the influence of internet celebrities on the market and the public. However, the rise of internet celebrities not only drives the development of the industry, but also affects the thoughts and behaviors of audience, resulting in Emotional Contagion.The establishment of digital footprints make the data collection of big data research more convenient than social media research in the past. But big data simplifies the emotions or stories in the data, making it difficult for researchers to gain a deeper understanding of user context. Thick data increases the thickness of data, which can solve the problem of big data data invisibly eliminating the background, story or meaning contained in the data, and understand the real side of human life.In order to analyze how internet celebrities have emotional contagion effects on audience through video contents. This study focuses on four types of internet celebrities in Taiwan, including life entertainment, advertorial and marketing, knowledge and information, news and politics. Through big data combined with the thick data manual collection method, we collected a total of 810 videos as samples and constructed video categories.The results of the analysis show that internet celebrities can influence the audience to have similar emotions through the emotional expression of videos. Moreover, the news and political issues of marketing techniques used by internet celebrities in the videos will indeed affect the positive and negative emotions or attitudes of the audience. And life entertainment, advertorial and marketing, knowledge and information internet celebrities are more likely to arouse positive emotions from the audience, while news and politics internet celebrities are more likely to arouse negative emotions from the audience.However, we also found that the contagious force of negative emotions is greater when the proportion of positive and negative emotions in the film is similar from the video samples of news and politics internet celebrities.In addition, in the sampled videos of the content of the COVID-19 epidemic, we observed that internet celebrities are indeed affected by major events to make videos, and in the same video theme, the emotions and attitudes of internet celebrities in the videos will change the emotions and attitudes of the audience.參考文獻 一、中文文獻InsightXplorer 創市際市場研究顧問（2022）。2020 至 2021 年台灣網路行為趨勢觀察與比較。2022年2月15日，取自：https://www.ixresearch.com/reports/創市際雙週刊第一九三期-20220215/王韋堯、黃詩珮、劉怡寧（2012）。消費品廣告設計之情緒效價與喚起分析。設計學報 (Journal of Design)，17(3)。王嘉慶（2021）。2021 YouTube Brandcast：能見度及心佔率成品牌溝通關鍵，2022年3月10日。取自：https://taiwan.googleblog.com/2021/10/youtube-brandcast-2021.html王馥蓓（2018年01月10日）。Youtuber、網紅當道，品牌究竟何去何從？。2022年06月10日，取自：https://www.cw.com.tw/article/5087508王瀟、李文忠、杜建剛（2010）。情緒感染理論研究述評。心理科學進展。18(8)，1236-1245。KOL Rader、數位時代（2021）。百大影響力網紅數據洞察報告書。2022年1月20日，取自：https://www.kolradar.com/reports/2021-top100-kol宋世祥（2016）。百工裡的人類學家：帶你挖掘「厚數據」，以人類學之眼洞悉人性，引領社會創新！。台灣：果力文化出版。何振誠、邱張名琪、陳威助（2009）。從網誌到微網誌: 網路社會參與型態的演變介紹。資訊社會研究，17，1-51。林郁翔、任立中（2019）。品牌粉絲專業之社群情感氛圍初探。管理與系統，26(1)，79-112。林庭安（2020）消費需求藏在數據裡！以人類學視角洞察數據的 3 種工具，幫你看穿消費者情感、思維。經理人，2022年3月25日，取自：https://www.managertoday.com.tw/articles/view/60370李胤綺（2020）。網紅為政治背書之效果研究。開南學報，27-36。周得媛、康學真、呂佳妍、謝泓晉（2019）網路紅人可信度影響消費者態度之研究-以 YouTube 表演類網紅為例，圖文傳播藝術學報，87-101。財團法人台灣網路資訊中心（2020）。2020台灣網路報告，取自：https://report.twnic.tw/2020/凌品葳（2018）。YouTuber類型與廣告價值對消費者反應之影響：以幽默程度作為調節變數。﹝碩士論文。國立中央大學﹞臺灣博碩士論文知識加值系統。 https://hdl.handle.net/11296/8p6uqw。施伯燁（2014）。社群媒體-使用者研究之概念，方法與方法論初探。傳播研究與實踐，4(2)，207-227。姜凱恩、洪珮珊、李欣蔚、張家馨（2020）。探討年輕族群觀看 YOUTUBE 影片類型偏好和心理動機。圖文傳播藝術學報，137-144。袁國寶、謝利明（2016）。網紅經濟:移動互聯網時代的千億紅利市場，台北：商周出版。陳思涵（2018）。網紅特質對業配效果影響之研究—以美妝品為例。國立中興大學行銷學系所碩士論文，台中市。陳婉綾、郭宗賢、田寒光（2021）網紅與粉絲關係品質，信任轉移與自我監控對品牌推薦影響之研究。行銷科學學報，17(1)，67-88。黃友柔（2018），台灣美妝 YouTuber 影片呈現方式對消費者記憶度、喜好度、購買意願之影響，輔仁大學大眾傳播學研究所碩士論文。黃從仁（2020）。大數據與人工智慧方法在行為與社會科學的應用趨勢。調查研究-方法與應用，(45)，11-42。曹家榮、陳昭宏（2022）。組裝行動與混成的情緒：Instagram使用者的憂鬱書寫、連結與共生。新聞學研究，(150)，97-148。程倚華（2021）。網紅人流、金流關鍵指標！「高互動」3大心法：話題、分眾、多平台。2022年4月9日。程倚華（2021）。獨家調查！2021台灣100大影響力網紅榜單，誰連續3年稱王？誰空降？。2022年1月20日，取自：https://www.bnext.com.tw/article/64752/2021-kol100楊運秀、郭芳伃（2017）網紅業配文的說服效果: 懷疑人格, 熟悉度及專業性的影響。行銷評論，14(2)，163-189。蔡政宏、邱惠芳、陳佳玲（2020）。熱門網紅影片內容製作模式之探索性研究。全球商業經營管理學報，(12)，77-88。劉正山（2019）。厚資料與意義探勘專刊導論。問題與研究，58(2)， i-vi。劉雨涵（2018）。你 follow 她了嗎? 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Social and Personality Psychology Compass, 4(5), 331–343.Watson, D., Clark, L. A., & Tellegen, A. (1988). Development and validation of brief measures of positive and negative affect: the PANAS scales. Journal of personality and social psychology, 54(6), 1063.Werner Geyser. (2022, February 7). The State of Influencer Marketing 2022: Benchmark Report. Influencer Marketing Hub. https://influencermarketinghub.com/influencer-marketing-benchmark-report/ZAC(2020, February). The New Rules of Social. https://www.zakagency.com/wp-content/uploads/2020/02/J2097_WP3_TheNewRulesOfSocial_Compressed.pdf 描述 碩士
國立政治大學
傳播學院傳播碩士學位學程
109464016資料來源 http://thesis.lib.nccu.edu.tw/record/#G0109464016 資料類型 thesis dc.contributor.advisor 許志堅 zh_TW dc.contributor.advisor Sheu, Jyh-Jian en_US dc.contributor.author (作者) 莊喬羽 zh_TW dc.contributor.author (作者) Chuang, Chiao-Yu en_US dc.creator (作者) 莊喬羽 zh_TW dc.creator (作者) Chuang, Chiao-Yu en_US dc.date (日期) 2023 en_US dc.date.accessioned 2-八月-2023 14:09:21 (UTC+8) - dc.date.available 2-八月-2023 14:09:21 (UTC+8) - dc.date.issued (上傳時間) 2-八月-2023 14:09:21 (UTC+8) - dc.identifier (其他 識別碼) G0109464016 en_US dc.identifier.uri (URI) http://nccur.lib.nccu.edu.tw/handle/140.119/146591 - dc.description (描述) 碩士 zh_TW dc.description (描述) 國立政治大學 zh_TW dc.description (描述) 傳播學院傳播碩士學位學程 zh_TW dc.description (描述) 109464016 zh_TW dc.description.abstract (摘要) 2020年起，受到Covid-19疫情影響，人們進行遠端學習與線上互動的比率大幅提升。台灣民眾使用Youtube平台觀看影片的頻率上升，促進網路紅人（internet celebrity）職業的崛起。網紅進行更加多元化的創作，並快速累積粉絲數，甚至企業與品牌也會邀請網紅拍攝廣告或業配，顯示網紅對市場和民眾的影響力。然而，網紅除了帶動產業發展外，也會影響閱聽人的思想與行為，形成情緒渲染（emotional contagion）現象。在過去社群媒體的研究中，由於數位足跡（digital footprint）的建立，使大數據研究的資料蒐集更便利。然而，大數據簡化資料中的情感或故事，使研究者難以深入了解使用者脈絡。厚數據（thick data）透過增加資料厚度的方式，除了解決大數據無形中剔除資料中所包含的背景、故事或意義的問題，也能了解人的真實需求。本研究為分析網紅如何透過影音內容對閱聽人產生情緒渲染效果，以生活娛樂、業配行銷、知識資訊、時事與政治等台灣的四大類型網紅為主，結合大數據和厚數據研究方法增厚數位足跡資料，蒐集總計810部影片樣本資料，來建構影片類目並進行資料分析。經分析結果顯示，網紅可以透過影音內容的情緒表述影響閱聽人產生相似的情緒，且網紅在影片中所使用的新聞時事與政治議題行銷操作手法確實會影響閱聽人的正、負向情緒或態度。其中業配行銷、知識資訊、生活娛樂型網紅較常引起閱聽人的正向情緒，時事與政治型網紅的影片則較常引發閱聽人的負向情緒。不過，從時事與政治型網紅的影片樣本中，我們也發現當影片中的正向和負向情緒比例相近時，負向情緒的感染力更大。此外，在疫情內容主題取樣的影片中，我們觀察到網紅確實會受到重大事件的影響製作影片，並且在相同的影片題材中，網紅在影片中的情緒與態度會改變閱聽人的情緒或態度。 zh_TW dc.description.abstract (摘要) Due to Covid-19, Taiwanese have significantly increased the rate of remote learning and online interaction since 2020. Taiwanese users use Youtube more frequently to watch video contents, which has promoted the rise of the career of internet celebrities. Internet celebrities carry out more diversified creations and quickly accumulate fans. Even enterprises and brands will invite internet celebrities to film the advertisement or create advertorials, showing the influence of internet celebrities on the market and the public. However, the rise of internet celebrities not only drives the development of the industry, but also affects the thoughts and behaviors of audience, resulting in Emotional Contagion.The establishment of digital footprints make the data collection of big data research more convenient than social media research in the past. But big data simplifies the emotions or stories in the data, making it difficult for researchers to gain a deeper understanding of user context. Thick data increases the thickness of data, which can solve the problem of big data data invisibly eliminating the background, story or meaning contained in the data, and understand the real side of human life.In order to analyze how internet celebrities have emotional contagion effects on audience through video contents. This study focuses on four types of internet celebrities in Taiwan, including life entertainment, advertorial and marketing, knowledge and information, news and politics. Through big data combined with the thick data manual collection method, we collected a total of 810 videos as samples and constructed video categories.The results of the analysis show that internet celebrities can influence the audience to have similar emotions through the emotional expression of videos. Moreover, the news and political issues of marketing techniques used by internet celebrities in the videos will indeed affect the positive and negative emotions or attitudes of the audience. And life entertainment, advertorial and marketing, knowledge and information internet celebrities are more likely to arouse positive emotions from the audience, while news and politics internet celebrities are more likely to arouse negative emotions from the audience.However, we also found that the contagious force of negative emotions is greater when the proportion of positive and negative emotions in the film is similar from the video samples of news and politics internet celebrities.In addition, in the sampled videos of the content of the COVID-19 epidemic, we observed that internet celebrities are indeed affected by major events to make videos, and in the same video theme, the emotions and attitudes of internet celebrities in the videos will change the emotions and attitudes of the audience. en_US dc.description.tableofcontents 第一章 緒論 1第一節 研究背景與動機 1第二節 研究目的 5第二章 文獻回顧 9第一節 網路紅人 9第二節 社群媒體 17第三節 情緒渲染 23第四節 厚數據 29第三章 研究方法 32第一節 研究架構 32第二節 研究設計 33第四章 資料分析 42第一節 資料樣本整體分布與趨勢 42第二節 不同類型網紅影片之行為分析 46第三節 以COVID-19疫情為例比較不同類型網紅之行為 70第五章 結論與建議 94第一節 研究討論與建議 94第二節 研究限制 101參考文獻 102 zh_TW dc.format.extent 3393450 bytes - dc.format.mimetype application/pdf - dc.source.uri (資料來源) http://thesis.lib.nccu.edu.tw/record/#G0109464016 en_US dc.subject (關鍵詞) 厚數據 zh_TW dc.subject (關鍵詞) 大數據 zh_TW dc.subject (關鍵詞) 情緒渲染 zh_TW dc.subject (關鍵詞) 網紅 zh_TW dc.subject (關鍵詞) 社群媒體 zh_TW dc.subject (關鍵詞) thick data en_US dc.subject (關鍵詞) big data en_US dc.subject (關鍵詞) emotional contagion en_US dc.subject (關鍵詞) internet celebrity en_US dc.subject (關鍵詞) social media en_US dc.title (題名) 結合大數據與厚數據方法觀察社群媒介上網紅對閱聽人的情緒渲染效果 zh_TW dc.title (題名) Combining Big Data and Thick Data Methods to Analyze the Emotional Contagion Effect of Social Media Influencers on Audience en_US dc.type (資料類型) thesis en_US dc.relation.reference (參考文獻) 一、中文文獻InsightXplorer 創市際市場研究顧問（2022）。2020 至 2021 年台灣網路行為趨勢觀察與比較。2022年2月15日，取自：https://www.ixresearch.com/reports/創市際雙週刊第一九三期-20220215/王韋堯、黃詩珮、劉怡寧（2012）。消費品廣告設計之情緒效價與喚起分析。設計學報 (Journal of Design)，17(3)。王嘉慶（2021）。2021 YouTube Brandcast：能見度及心佔率成品牌溝通關鍵，2022年3月10日。取自：https://taiwan.googleblog.com/2021/10/youtube-brandcast-2021.html王馥蓓（2018年01月10日）。Youtuber、網紅當道，品牌究竟何去何從？。2022年06月10日，取自：https://www.cw.com.tw/article/5087508王瀟、李文忠、杜建剛（2010）。情緒感染理論研究述評。心理科學進展。18(8)，1236-1245。KOL Rader、數位時代（2021）。百大影響力網紅數據洞察報告書。2022年1月20日，取自：https://www.kolradar.com/reports/2021-top100-kol宋世祥（2016）。百工裡的人類學家：帶你挖掘「厚數據」，以人類學之眼洞悉人性，引領社會創新！。台灣：果力文化出版。何振誠、邱張名琪、陳威助（2009）。從網誌到微網誌: 網路社會參與型態的演變介紹。資訊社會研究，17，1-51。林郁翔、任立中（2019）。品牌粉絲專業之社群情感氛圍初探。管理與系統，26(1)，79-112。林庭安（2020）消費需求藏在數據裡！以人類學視角洞察數據的 3 種工具，幫你看穿消費者情感、思維。經理人，2022年3月25日，取自：https://www.managertoday.com.tw/articles/view/60370李胤綺（2020）。網紅為政治背書之效果研究。開南學報，27-36。周得媛、康學真、呂佳妍、謝泓晉（2019）網路紅人可信度影響消費者態度之研究-以 YouTube 表演類網紅為例，圖文傳播藝術學報，87-101。財團法人台灣網路資訊中心（2020）。2020台灣網路報告，取自：https://report.twnic.tw/2020/凌品葳（2018）。YouTuber類型與廣告價值對消費者反應之影響：以幽默程度作為調節變數。﹝碩士論文。國立中央大學﹞臺灣博碩士論文知識加值系統。 https://hdl.handle.net/11296/8p6uqw。施伯燁（2014）。社群媒體-使用者研究之概念，方法與方法論初探。傳播研究與實踐，4(2)，207-227。姜凱恩、洪珮珊、李欣蔚、張家馨（2020）。探討年輕族群觀看 YOUTUBE 影片類型偏好和心理動機。圖文傳播藝術學報，137-144。袁國寶、謝利明（2016）。網紅經濟:移動互聯網時代的千億紅利市場，台北：商周出版。陳思涵（2018）。網紅特質對業配效果影響之研究—以美妝品為例。國立中興大學行銷學系所碩士論文，台中市。陳婉綾、郭宗賢、田寒光（2021）網紅與粉絲關係品質，信任轉移與自我監控對品牌推薦影響之研究。行銷科學學報，17(1)，67-88。黃友柔（2018），台灣美妝 YouTuber 影片呈現方式對消費者記憶度、喜好度、購買意願之影響，輔仁大學大眾傳播學研究所碩士論文。黃從仁（2020）。大數據與人工智慧方法在行為與社會科學的應用趨勢。調查研究-方法與應用，(45)，11-42。曹家榮、陳昭宏（2022）。組裝行動與混成的情緒：Instagram使用者的憂鬱書寫、連結與共生。新聞學研究，(150)，97-148。程倚華（2021）。網紅人流、金流關鍵指標！「高互動」3大心法：話題、分眾、多平台。2022年4月9日。程倚華（2021）。獨家調查！2021台灣100大影響力網紅榜單，誰連續3年稱王？誰空降？。2022年1月20日，取自：https://www.bnext.com.tw/article/64752/2021-kol100楊運秀、郭芳伃（2017）網紅業配文的說服效果: 懷疑人格, 熟悉度及專業性的影響。行銷評論，14(2)，163-189。蔡政宏、邱惠芳、陳佳玲（2020）。熱門網紅影片內容製作模式之探索性研究。全球商業經營管理學報，(12)，77-88。劉正山（2019）。厚資料與意義探勘專刊導論。問題與研究，58(2)， i-vi。劉雨涵（2018）。你 follow 她了嗎? 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