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題名 假新聞研究趨勢及書目計量學分析
Fake News: Research Trends and A Bibliometric Analysis作者 郭庭瑋
Kuo, Ting-Wei貢獻者 梁定澎<br>彭志宏
Liang, Ting-Peng<br>Peng, Chih-Hung
郭庭瑋
Kuo, Ting-Wei關鍵詞 假新聞
書目計量學
系統性分析
趨勢
學門
Fake News
Bibliometric Analysis
System Analysis
Trends
Discipline日期 2021 上傳時間 2-九月-2021 15:48:47 (UTC+8) 摘要 假新聞(fake news)一詞在2016年美國總統大選後被大家廣為使用，人們自從劍橋分析事件(Cambridge Analytica)之後開始逐漸重視假新聞所帶來的危害，2019年底遭逢COVID-19開始在全球肆虐，關於此疾病的假新聞大量的出現在各個媒體上，也使得假新聞進入了另一個高峰期。假新聞的研究主題有很多，目前僅有部分學者針對特定的主題做小範圍的分析，尚未有學者針對所有類型的文獻一個較有統整性的整理，因此本研究透過蒐集在Web of Science上蒐集假新聞的相關文獻，並透過書目計量學分析(Bibliometric Analysis)，去探討這些文獻，本研究以書目計量的輔助軟體(VOSviewer)完成相關的分析，透過作者給予文獻的關鍵字去了解目前的研究趨勢，並且將這些結果可視化，本研究也將蒐集而來的文獻進行學門的分群，對於不同學門的文獻內容做了進一步的分析，在最後也提出了了解假新聞研究領域閱讀文獻的推薦順序，供後續的研究人員作參考。
The phrase “fake news” has become popular in the wake of the United States presidential election of 2016. People became concerned about the dangers that could be caused by fake news ever since the Cambridge Analytica scandal. During the COVID-19 outbreak at the end of 2019, fake news about the disease rapidly spread across various media outlets, leading to a new peak in fake news.There are many studies on fake news. In the current studies, researchers have only analyzed certain topics on a small scale, so this study set out to analyze all types of sources. This study collected studies about fake news from a website called Web of Science (WOS), and this study used bibliometric analysis to analyze the research. This study used a software called VOSviewer to help us complete the bibliometric analysis, recognize the research trends via author keywords, and visualize the results. This study also sorted the studies by research areas and analyzed them. Lastly, this study proposed a reading sequence for the studies for future researchers.參考文獻 汪志堅、陳才(民108)。假新聞來源、樣態與因應策略。新北市:前程文化。Albright, J. (2017). Welcome to the Era of Fake News [Editorial Material]. Media and Communication, 5(2), 87-89.Allcott, H., & Gentzkow, M. (2017). Social Media and Fake News in the 2016 Election. Journal of Economic Perspectives, 31(2), 211-236.Ardito, L., Scuotto, V., Del Giudice, M., & Petruzzelli, A. M. (2019). A bibliometric analysis of research on Big Data analytics for business and management. Management Decision, 57(8), 1993-2009.Chen, A. (2017). “The Fake-News Fallacy.” The New Yorker, September 5. https://www.newyorker.com/magazine/2017/09/04/the-fake-news-fallacy?utm_content=bufferfc8ed&utm_medium=social&utm_source=twitter.com&utm_campaign=bufferChen, C. (2004). Searching for intellectual turning points: Progressive knowledge domain visualization. Proceedings of the National Academy of Sciences, 101(suppl 1), 5303.Chen, C. (2006). CiteSpace II: Detecting and visualizing emerging trends and transient patterns in scientific literature. Journal of the American Society for Information Science and Technology, 57(3), 359-377.Constine, J., & Hatmaker, T. (2018). Facebook admits Cambridge Analytica hijacked data on up to 87 m users. TechCrunch. Retrieved from https://techcrunch.com/2018/04/04/cambridge-analytica-87-million/Corner, J. (2017). Fake news, post-truth and media–political change. Media, Culture & Society, 39(7), 1100–1107.Edson C. Tandoc Jr., Zheng Wei Lim & Richard Ling (2018) Defining “Fake News”, Digital Journalism, 6:2, 137-153, DOI: 10.1080/21670811.2017.1360143Ghanem, B., Rosso, P., & Rangel, F. (2020). An Emotional Analysis of False Information in Social Media and News Articles [Article]. Acm Transactions on Internet Technology, 20(2), 18, Article 19. https://doi.org/10.1145/3381750Grinberg, N., Joseph, K., Friedland, L., Swire-Thompson, B., & Lazer, D. (2019). Fake news on Twitter during the 2016 US presidential election [Article]. Science, 363(6425), 374-+. https://doi.org/10.1126/science.aau2706Guess, A., Nagler, J., & Tucker, J. (2019). Less than you think: Prevalence and predictors of fake news dissemination on Facebook [Article]. Science Advances, 5(1), 8, Article eaau4586. https://doi.org/10.1126/sciadv.aau4586Hartley, J. (1996). Popular Reality: Journalism, Modernity, Popular Culture.Hermida, A. (2010). Twittering the news. Journalism Practice, 4, 297-308. https://doi.org/10.1080/17512781003640703Hermida, A. (2011). Fluid Spaces, Fluid Journalism. In Participatory Journalism (eds J.B. Singer, A. Hermida, D. Domingo, A. Heinonen, S. Paulussen, T. Quandt, Z. Reich and M. Vujnovic). https://doi.org/10.1002/9781444340747.ch10Howard, P. N., & Kollanyi, B. (2016). Bots, #StrongerIn, and #Brexit: ComputationalPropaganda during the UK-EU Referendum. arXiv:1606.06356 [Physics].Retrieved from http://arxiv.org/abs/1606.06356Hunt, K., Agarwal, P., & Zhuang, J. Monitoring Misinformation on Twitter During Crisis Events: A Machine Learning Approach [Article; Early Access]. Risk Analysis, 21. https://doi.org/10.1111/risa.13634Jewitt, R. (2009). The trouble with twittering: integrating social media into mainstream news. International Journal of Media and Cultural Politics, 5 (3). pp. 231-238.Khan, K. S., Kunz, R., Kleijnen, J., & Antes, G. (2003). Five Steps to Conducting a Systematic Review. Journal of the Royal Society of Medicine, 96(3), 118–121.Kiernan, L. (2017). “‘Frondeurs’ and fake news: how misinformation ruled in 17th-century France.” The Local, August 15. https://www.thelocal.fr/20170815/frondeurs-and-fakenews-how-misinformation-ruled-in-17th-century-france.Ripoll, L., & Matos, J. (2020). Information reliability: criteria to identify misinformation in the digital environment. Investigación Bibliotecológica: archivonomía, bibliotecología e información, 34, 79.Robinson, S., & DeShano, C. (2011). ‘Anyone can know’: Citizen journalism and the interpretive community of the mainstream press. Journalism, 12(8), 963–982. https://doi.org/10.1177/1464884911415973Sippitt, A., & Moy, W. (2020). Fact Checking is About What we Change not Just Who we Reach [Article]. Political Quarterly, 91(3), 592-595. https://doi.org/10.1111/1467-923x.12898Tandoc, E. C., Lim, Z. W., & Ling, R. (2018). DEFINING "FAKE NEWS" A typology of scholarly definitions [Article]. Digital Journalism, 6(2), 137-153. https://doi.org/10.1080/21670811.2017.1360143The Onion. (2017c). “Tearful Biden Carefully Takes Down Blacklight Poster of Topless Barbarian Chick From Office Wall.” The Onion 53 (2). https://www.theonion.com/article/tearfulbiden-carefully-takes-down-blacklight-post-55089.van Eck, N. J., & Waltman, L. (2010). Software survey: VOSviewer, a computer program for bibliometric mapping. Scientometrics, 84(2), 523-538.van Eck, N. J., Waltman, L., Dekker, R., & van den Berg, J. (2010). A comparison of two techniques for bibliometric mapping: Multidimensional scaling and VOS. Journal of the American Society for Information Science and Technology, 61(12), 2405-2416.van Eck, N. J., Waltman, L., Noyons, E. C. M., & Buter, R. K. (2010). Automatic term identification for bibliometric mapping. Scientometrics, 82(3), 581-596.Wang, M., Rao, M. K., & Sun, Z. P. Typology, Etiology, and Fact-Checking: A Pathological Study of Top Fake News in China [Article; Early Access]. Journalism Practice, 19. https://doi.org/10.1080/17512786.2020.1806723Wang, Y. X., McKee, M., Torbica, A., & Stuckler, D. (2019). Systematic Literature Review on the Spread of Health-related Misinformation on Social Media [Review]. Social Science & Medicine, 240, 12, Article 112552. https://doi.org/10.1016/j.socscimed.2019.112552Wardle, C. (2017). “Fake News.” It’s Complicated. https://medium.com/1st-draft/fake-newsits-complicated-d0f773766c79.Zupic, I., & Čater, T. (2015). Bibliometric Methods in Management and Organization. Organizational Research Methods, 18(3), 429–472. 描述 碩士
國立政治大學
資訊管理學系
108356001資料來源 http://thesis.lib.nccu.edu.tw/record/#G0108356001 資料類型 thesis dc.contributor.advisor 梁定澎<br>彭志宏 zh_TW dc.contributor.advisor Liang, Ting-Peng<br>Peng, Chih-Hung en_US dc.contributor.author (作者) 郭庭瑋 zh_TW dc.contributor.author (作者) Kuo, Ting-Wei en_US dc.creator (作者) 郭庭瑋 zh_TW dc.creator (作者) Kuo, Ting-Wei en_US dc.date (日期) 2021 en_US dc.date.accessioned 2-九月-2021 15:48:47 (UTC+8) - dc.date.available 2-九月-2021 15:48:47 (UTC+8) - dc.date.issued (上傳時間) 2-九月-2021 15:48:47 (UTC+8) - dc.identifier (其他 識別碼) G0108356001 en_US dc.identifier.uri (URI) http://nccur.lib.nccu.edu.tw/handle/140.119/136840 - dc.description (描述) 碩士 zh_TW dc.description (描述) 國立政治大學 zh_TW dc.description (描述) 資訊管理學系 zh_TW dc.description (描述) 108356001 zh_TW dc.description.abstract (摘要) 假新聞(fake news)一詞在2016年美國總統大選後被大家廣為使用，人們自從劍橋分析事件(Cambridge Analytica)之後開始逐漸重視假新聞所帶來的危害，2019年底遭逢COVID-19開始在全球肆虐，關於此疾病的假新聞大量的出現在各個媒體上，也使得假新聞進入了另一個高峰期。假新聞的研究主題有很多，目前僅有部分學者針對特定的主題做小範圍的分析，尚未有學者針對所有類型的文獻一個較有統整性的整理，因此本研究透過蒐集在Web of Science上蒐集假新聞的相關文獻，並透過書目計量學分析(Bibliometric Analysis)，去探討這些文獻，本研究以書目計量的輔助軟體(VOSviewer)完成相關的分析，透過作者給予文獻的關鍵字去了解目前的研究趨勢，並且將這些結果可視化，本研究也將蒐集而來的文獻進行學門的分群，對於不同學門的文獻內容做了進一步的分析，在最後也提出了了解假新聞研究領域閱讀文獻的推薦順序，供後續的研究人員作參考。 zh_TW dc.description.abstract (摘要) The phrase “fake news” has become popular in the wake of the United States presidential election of 2016. People became concerned about the dangers that could be caused by fake news ever since the Cambridge Analytica scandal. During the COVID-19 outbreak at the end of 2019, fake news about the disease rapidly spread across various media outlets, leading to a new peak in fake news.There are many studies on fake news. In the current studies, researchers have only analyzed certain topics on a small scale, so this study set out to analyze all types of sources. This study collected studies about fake news from a website called Web of Science (WOS), and this study used bibliometric analysis to analyze the research. This study used a software called VOSviewer to help us complete the bibliometric analysis, recognize the research trends via author keywords, and visualize the results. This study also sorted the studies by research areas and analyzed them. Lastly, this study proposed a reading sequence for the studies for future researchers. en_US dc.description.tableofcontents 謝辭 II摘要 IIIAbstract IV目次 I表次 IV圖次 V第一章 緒論 1第一節 研究背景 1第二節 研究動機 2第三節 研究目的 2第四節 研究流程 3第二章 文獻回顧 5第一節 什麼是假新聞 5第二節 社群媒體上的假新聞 7第三節 如何辨別假新聞 7第四節 書目計量學 9一、 書目計量學的基本概念 10二、 書目計量學的量化方法 10三、 書目計量學的輔助軟體 12四、 書目計量學的相關採用文獻 13第三章 研究方法 14第一節 採用研究工具 14一、 文獻資料庫平台 14二、 書目計量學輔助分析軟體 14第二節 選擇研究項目 15一、 假新聞的研究主題及研究趨勢 15二、 假新聞文獻的研究主體 15第三節 選擇分析方式 16第四節 文獻資料及檢索策略 17一、 關鍵字選擇 17二、 年份選擇 17第四章 研究趨勢與書目計量結果 18第一節 假新聞文獻的發表趨勢 18第二節 作者關鍵字分析 19一、 SOCIOLOGY(社會學) 28二、 COMPUTER SCIENCE INFORMATION SYSTEMS(電腦科學與資訊系統) 33三、 POLITICAL SCIENCE(政治科學) 39四、 INFORMATION SCIENCE LIBRARY SCIENCE(資訊科學與圖書館科學) 46五、 COMMUNICATION(傳播學) 56六、 五個學門之間相互引用的情形 69七、 作者關鍵字的年份變化 70第三節 文獻被引用分析 75第四節 共同作者分析 78第五節 文獻書目耦合分析 80第六節 文獻共被引用分析 83第五章 結論與建議 87第一節 研究結論 87一、 假新聞的研究主題 87二、 假新聞的研究趨勢 90第二節 研究貢獻 91一、 理論層面貢獻 91二、 實務層面貢獻 92第三節 研究限制 92第四節 未來方向 92參考文獻 94附錄:書目計量學分析資料 98 zh_TW dc.format.extent 5837044 bytes - dc.format.mimetype application/pdf - dc.source.uri (資料來源) http://thesis.lib.nccu.edu.tw/record/#G0108356001 en_US dc.subject (關鍵詞) 假新聞 zh_TW dc.subject (關鍵詞) 書目計量學 zh_TW dc.subject (關鍵詞) 系統性分析 zh_TW dc.subject (關鍵詞) 趨勢 zh_TW dc.subject (關鍵詞) 學門 zh_TW dc.subject (關鍵詞) Fake News en_US dc.subject (關鍵詞) Bibliometric Analysis en_US dc.subject (關鍵詞) System Analysis en_US dc.subject (關鍵詞) Trends en_US dc.subject (關鍵詞) Discipline en_US dc.title (題名) 假新聞研究趨勢及書目計量學分析 zh_TW dc.title (題名) Fake News: Research Trends and A Bibliometric Analysis en_US dc.type (資料類型) thesis en_US dc.relation.reference (參考文獻) 汪志堅、陳才(民108)。假新聞來源、樣態與因應策略。新北市:前程文化。Albright, J. (2017). Welcome to the Era of Fake News [Editorial Material]. Media and Communication, 5(2), 87-89.Allcott, H., & Gentzkow, M. (2017). Social Media and Fake News in the 2016 Election. Journal of Economic Perspectives, 31(2), 211-236.Ardito, L., Scuotto, V., Del Giudice, M., & Petruzzelli, A. M. (2019). A bibliometric analysis of research on Big Data analytics for business and management. Management Decision, 57(8), 1993-2009.Chen, A. (2017). “The Fake-News Fallacy.” The New Yorker, September 5. https://www.newyorker.com/magazine/2017/09/04/the-fake-news-fallacy?utm_content=bufferfc8ed&utm_medium=social&utm_source=twitter.com&utm_campaign=bufferChen, C. (2004). Searching for intellectual turning points: Progressive knowledge domain visualization. Proceedings of the National Academy of Sciences, 101(suppl 1), 5303.Chen, C. (2006). CiteSpace II: Detecting and visualizing emerging trends and transient patterns in scientific literature. Journal of the American Society for Information Science and Technology, 57(3), 359-377.Constine, J., & Hatmaker, T. (2018). Facebook admits Cambridge Analytica hijacked data on up to 87 m users. TechCrunch. Retrieved from https://techcrunch.com/2018/04/04/cambridge-analytica-87-million/Corner, J. (2017). Fake news, post-truth and media–political change. Media, Culture & Society, 39(7), 1100–1107.Edson C. Tandoc Jr., Zheng Wei Lim & Richard Ling (2018) Defining “Fake News”, Digital Journalism, 6:2, 137-153, DOI: 10.1080/21670811.2017.1360143Ghanem, B., Rosso, P., & Rangel, F. (2020). An Emotional Analysis of False Information in Social Media and News Articles [Article]. Acm Transactions on Internet Technology, 20(2), 18, Article 19. https://doi.org/10.1145/3381750Grinberg, N., Joseph, K., Friedland, L., Swire-Thompson, B., & Lazer, D. (2019). Fake news on Twitter during the 2016 US presidential election [Article]. Science, 363(6425), 374-+. https://doi.org/10.1126/science.aau2706Guess, A., Nagler, J., & Tucker, J. (2019). Less than you think: Prevalence and predictors of fake news dissemination on Facebook [Article]. Science Advances, 5(1), 8, Article eaau4586. https://doi.org/10.1126/sciadv.aau4586Hartley, J. (1996). Popular Reality: Journalism, Modernity, Popular Culture.Hermida, A. (2010). Twittering the news. Journalism Practice, 4, 297-308. https://doi.org/10.1080/17512781003640703Hermida, A. (2011). Fluid Spaces, Fluid Journalism. In Participatory Journalism (eds J.B. Singer, A. Hermida, D. Domingo, A. Heinonen, S. Paulussen, T. Quandt, Z. Reich and M. Vujnovic). https://doi.org/10.1002/9781444340747.ch10Howard, P. N., & Kollanyi, B. (2016). Bots, #StrongerIn, and #Brexit: ComputationalPropaganda during the UK-EU Referendum. arXiv:1606.06356 [Physics].Retrieved from http://arxiv.org/abs/1606.06356Hunt, K., Agarwal, P., & Zhuang, J. Monitoring Misinformation on Twitter During Crisis Events: A Machine Learning Approach [Article; Early Access]. Risk Analysis, 21. https://doi.org/10.1111/risa.13634Jewitt, R. (2009). The trouble with twittering: integrating social media into mainstream news. International Journal of Media and Cultural Politics, 5 (3). pp. 231-238.Khan, K. S., Kunz, R., Kleijnen, J., & Antes, G. (2003). Five Steps to Conducting a Systematic Review. Journal of the Royal Society of Medicine, 96(3), 118–121.Kiernan, L. (2017). “‘Frondeurs’ and fake news: how misinformation ruled in 17th-century France.” The Local, August 15. https://www.thelocal.fr/20170815/frondeurs-and-fakenews-how-misinformation-ruled-in-17th-century-france.Ripoll, L., & Matos, J. (2020). Information reliability: criteria to identify misinformation in the digital environment. Investigación Bibliotecológica: archivonomía, bibliotecología e información, 34, 79.Robinson, S., & DeShano, C. (2011). ‘Anyone can know’: Citizen journalism and the interpretive community of the mainstream press. Journalism, 12(8), 963–982. https://doi.org/10.1177/1464884911415973Sippitt, A., & Moy, W. (2020). Fact Checking is About What we Change not Just Who we Reach [Article]. Political Quarterly, 91(3), 592-595. https://doi.org/10.1111/1467-923x.12898Tandoc, E. C., Lim, Z. W., & Ling, R. (2018). DEFINING "FAKE NEWS" A typology of scholarly definitions [Article]. Digital Journalism, 6(2), 137-153. https://doi.org/10.1080/21670811.2017.1360143The Onion. (2017c). “Tearful Biden Carefully Takes Down Blacklight Poster of Topless Barbarian Chick From Office Wall.” The Onion 53 (2). https://www.theonion.com/article/tearfulbiden-carefully-takes-down-blacklight-post-55089.van Eck, N. J., & Waltman, L. (2010). Software survey: VOSviewer, a computer program for bibliometric mapping. Scientometrics, 84(2), 523-538.van Eck, N. J., Waltman, L., Dekker, R., & van den Berg, J. (2010). A comparison of two techniques for bibliometric mapping: Multidimensional scaling and VOS. Journal of the American Society for Information Science and Technology, 61(12), 2405-2416.van Eck, N. J., Waltman, L., Noyons, E. C. M., & Buter, R. K. (2010). Automatic term identification for bibliometric mapping. Scientometrics, 82(3), 581-596.Wang, M., Rao, M. K., & Sun, Z. P. Typology, Etiology, and Fact-Checking: A Pathological Study of Top Fake News in China [Article; Early Access]. Journalism Practice, 19. https://doi.org/10.1080/17512786.2020.1806723Wang, Y. X., McKee, M., Torbica, A., & Stuckler, D. (2019). Systematic Literature Review on the Spread of Health-related Misinformation on Social Media [Review]. Social Science & Medicine, 240, 12, Article 112552. https://doi.org/10.1016/j.socscimed.2019.112552Wardle, C. (2017). “Fake News.” It’s Complicated. https://medium.com/1st-draft/fake-newsits-complicated-d0f773766c79.Zupic, I., & Čater, T. (2015). Bibliometric Methods in Management and Organization. Organizational Research Methods, 18(3), 429–472. zh_TW dc.identifier.doi (DOI) 10.6814/NCCU202101434 en_US
