政大機構典藏-National Chengchi University Institutional Repository(NCCUR):Item 140.119/136840

政大機構典藏-National Chengchi University Institutional Repository(NCCUR):Item 140.119/136840

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题名:	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
贡献者:	梁定澎彭志宏 Liang, Ting-Peng Peng, Chih-Hung 郭庭瑋 Kuo, Ting-Wei
关键词:	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
上传时间:	2021-09-02 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=buffer Chen, 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: 10.1080/21670811.2017.1360143 Ghanem, 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/10.1145/3381750 Grinberg, 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.aau2706 Guess, 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.aau4586 Hartley, J. (1996). Popular Reality: Journalism, Modernity, Popular Culture. Hermida, A. (2010). Twittering the news. Journalism Practice, 4, 297-308. https://doi.org/10.1080/17512781003640703 Hermida, 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.ch10 Howard, 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/1606.06356 Hunt, 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.13634 Jewitt, 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/10.1177/1464884911415973 Sippitt, 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.12898 Tandoc, 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/10.1080/21670811.2017.1360143 The 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/10.1080/17512786.2020.1806723 Wang, 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.2019.112552 Wardle, 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
数据类型:	thesis
DOI:	10.6814/NCCU202101434
显示于类别:	[資訊管理學系] 學位論文

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