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題名 探討假新聞特徵標記及讀者認知風格對假新聞感知可信度之影響
Exploring the Effect of Fake News Characteristic Markings on the Perceived Credibility of Readers with Different Cognitive Style in Fake News作者 蘇晉威
Su, Jin-Wei貢獻者 梁定澎<br>彭志宏
Liang, Ting-Peng<br>Peng, Chih-Hung
蘇晉威
Su, Jin-Wei關鍵詞 假新聞特徵標記
認知反思測試
假新聞感知可信度日期 2021 上傳時間 2-Sep-2021 15:58:53 (UTC+8) 摘要 近年來,假新聞成為一個具有爭議性的議題,尤其在 2016 年美國總統大選期間和之後,人們對於此議題的重視更是與日俱增。並且由於社交媒體的普及,使得新思想的傳播更加便利,更加劇了其對民主、新聞環境和公眾信任的侵蝕。有鑑於假新聞議題的重要性,本研究將從受眾在閱讀新聞時的角度出發,試圖以一種網頁輔助系統新聞特徵標記的手段,協助受眾聚焦重要的新聞特徵,使其在遭遇假新聞時能降低其對該新聞的感知可信度。因此本研究將探討新聞網站進行假新聞特徵標記是否影響假新聞的感知可信度,並將認知反射測試的表現作為干擾變數,觀察其是否會干擾假新聞特徵標記與假新聞感知可信度之間的關聯。本研究使用問卷調查法在網路上發放問卷後,透過 SmartPLS 3 對回收之樣本以結構方程模式分析,並在確認研究之信度與效度後,對研究架構進行假說的檢定。研究結果發現假新聞特徵標記會負向顯著影響假新聞感知可信度,認知反射測試的干擾效果顯著。 參考文獻 Adipat, B., Zhang, D., & Zhou, L. (2011). The effects of tree-view based presentation adaptation on mobile web browsing. MIS Quarterly: Management Information Systems, 35(1), 99–121. https://doi.org/10.2307/23043491Anderson, J. C., & Gerbing, D. W. (1988). Structural Equation Modeling in Practice: A Review and Recommended Two-Step Approach. Psychological Bulletin, 103(3), 411–423. https://doi.org/10.1037/0033-2909.103.3.411Appelman, A., & Sundar, S. S. (2016). Measuring message credibility: Construction and validation of an exclusive scale. Journalism and Mass Communication Quarterly, 93(1), 59–79. https://doi.org/10.1177/1077699015606057Apuke, O. D., & Omar, B. (2021). Fake news and COVID-19: modelling the predictors of fake news sharing among social media users. Telematics and Informatics, 56(March), 101475. https://doi.org/10.1016/j.tele.2020.101475Baum, J., & Abdel Rahman, R. (2021). Emotional news affects social judgments independent of perceived media credibility. Social Cognitive and Affective Neuroscience, 16(3), 280–291. https://doi.org/10.1093/scan/nsaa164Baum, J., Frömer, R., & Rahman, R. A. (2020). Fake news and metacognition : Emotional contents enhance confidence in social judgments based on untrustworthy headlines. 1–24.Berger, J., & Milkman, K. L. (2012). What makes online content viral? Journal of Marketing Research, 49(2), 192–205. https://doi.org/10.1509/jmr.10.0353Borah, P. (2014). The hyperlinked world: A look at how the interactions of news frames and hyperlinks influence news credibility and willingness to seek information. Journal of Computer-Mediated Communication, 19(3), 576–590. https://doi.org/10.1111/jcc4.12060Bright, J. (2016). The Social News Gap: How News Reading and News Sharing Diverge. Journal of Communication, 66(3), 343–365. https://doi.org/10.1111/jcom.12232Bronstein, M. V., Pennycook, G., Bear, A., Rand, D. G., & Cannon, T. D. (2019). Belief in Fake News is Associated with Delusionality, Dogmatism, Religious Fundamentalism, and Reduced Analytic Thinking. Journal of Applied Research in Memory and Cognition, 8(1), 108–117. https://doi.org/10.1016/j.jarmac.2018.09.005Cao, J., Qi, P., Sheng, Q., Yang, T., Guo, J., & Li, J. (2020). Exploring the role of visual content in fake news detection. ArXiv, 141–161. https://doi.org/10.1007/978-3-030-42699-6_8Cruz, A., Rocha, G., Sousa-Silva, R., & Lopes Cardoso, H. (2019). Team Fernando- Pessa at SemEval-2019 Task 4: Back to Basics in Hyperpartisan News Detection. 999–1003. https://doi.org/10.18653/v1/s19-2173Duffy, A., Tandoc, E., & Ling, R. (2020). Too good to be true, too good not to share: the social utility of fake news. Information Communication and Society, 23(13), 1965–1979. https://doi.org/10.1080/1369118X.2019.1623904Dufrasne, M., Mercenier, H., & Wiard, V. (2020). Teens, social media and fake news: A user’s perspective.Epstein, S. (1994). Integration of the Cognitive and the Psychodynamic Unconscious. American Psychologist, 49(8), 709–724. https://doi.org/10.1037//0003- 066x.49.8.709Fornell, C., & Larcker, D. F. (1981). Fornell, C. and Larcker, D.F. (1981), “Evaluating structural equation models with unobservable variables and.pdf. Journal of Marketing Research, XVIII(February), 39–50.Frederick, S. (2005). Cognitive reflection and decision making. Journal of Economic Perspectives, 19(4), 25–42. https://doi.org/10.1257/089533005775196732Gao, G., Wang, H. C., Cosley, D., & Fussell, S. R. (2013). Same translation but different experience: The effects of highlighting on machine - Translated conversations. Conference on Human Factors in Computing Systems - Proceedings, 449–458. https://doi.org/10.1145/2470654.2470719Gaozhao, D. (2021). Flagging fake news on social media: An experimental study of media consumers’ identification of fake news. Government Information Quarterly, 38(March). https://doi.org/10.1016/j.giq.2021.101591Golbeck, J., Mauriello, M., Auxier, B., Bhanushali, K. H., Bonk, C., Bouzaghrane, M. A., Buntain, C., Chanduka, R., Cheakalos, P., Everett, J. B., Falak, W., Gieringer, C., Graney, J., Hoffman, K. M., Huth, L., Ma, Z., Jha, M., Khan, M., Kori, V., ... Visnansky, G. (2018). Fake news vs satire: A dataset and analysis. WebSci 2018 - Proceedings of the 10th ACM Conference on Web Science, 17– 21. https://doi.org/10.1145/3201064.3201100Gu, L., Kropotov, V., & Yarochkin, F. (2017). How Propagandists Abuse the Internet and Manipulate the Public. Trend Micro, 5, 1–81. https://documents.trendmicro.com/assets/white_papers/wp-fake-news-machine- how-propagandists-abuse-the-internet.pdfGunawan, F. E., & Suwandi, V. (2020). Identifying the most influencing characteristics of fake news. ICIC Express Letters, Part B: Applications, 11(1), 93–101. https://doi.org/10.24507/icicelb.11.01.93Haigh, M., Haigh, T., & Kozak, N. I. (2018). Stopping Fake News: The work practices of peer-to-peer counter propaganda. Journalism Studies, 19(14), 2062– 2087. https://doi.org/10.1080/1461670X.2017.1316681Horne, B. D., & Adalı, S. (2017). This just in: Fake news packs a lot in title, uses simpler, repetitive content in text body, more similar to satire than real news. ArXiv, 759–766.Hou, Z., Du, F., Jiang, H., Zhou, X., Lin, L., Assessment, T., & Commission, N. H. (2020). Assessment of public attention, risk perception, emotional and behavioural responses to the COVID-19 outbreak: social media surveillance in China.Huynh TL. (2020). The COVID-19 risk perception: A survey on socioeconomics and media attention. Economics Bulletin. . AccessEcon, 40(1(1), 758–764.Johnson, B. K. A., & Wiedenbeck, S. (2009). Perceived credibility of citizen journalism. Journalism & Mass Communication Quarterly, 82"(2), 332–348. http://jmq.sagepub.com.eresources.shef.ac.uk/content/86/2/332.full.pdf+htmlJones-Jang, S. M., Mortensen, T., & Liu, J. (2021). Does Media Literacy Help Identification of Fake News? Information Literacy Helps, but Other Literacies Don’t. American Behavioral Scientist, 65(2), 371–388. https://doi.org/10.1177/0002764219869406Juanchich, M., Dewberry, C., Sirota, M., & Narendran, S. (2016). Cognitive Reflection Predicts Real-Life Decision Outcomes, but Not Over and Above Personality and Decision-Making Styles. Journal of Behavioral Decision Making, 29(1), 52–59. https://doi.org/10.1002/bdm.1875Jungnickel, K. (2011). Nachrichtenqualität aus Nutzersicht. Medien & Kommunikationswissenschaft, 59(3), 360–378.Kahneman, D., & Frederick, S. (2012). Representativeness Revisited: Attribute Substitution in Intuitive Judgment. In Heuristics and Biases (Issue July 2002). https://doi.org/10.1017/cbo9780511808098.004Kanoh, H. (2018). Why do people believe in fake news over the Internet? Why do people believe in fake news over the Internet? An understanding from the perspective of existence of the habit of An understanding from the perspective of existence of the habit of eating and dr.Karlsson, M., & Clerwall, C. (2018). Transparency to the Rescue?: Evaluating citizens’ views on transparency tools in journalism. Journalism Studies, 19(13), 1923–1933. https://doi.org/10.1080/1461670X.2018.1492882Kim, H. S. (2015). Attracting Views and Going Viral: How Message Features and News-Sharing Channels Affect Health News Diffusion. Journal of Communication, 65(3), 512–534. https://doi.org/10.1111/jcom.12160Kiousis, S. (2001). Public Trust or Mistrust ? Perceptions of Media Credibility in the Information Age Public Trust or Mistrust ? Perceptions of Media Credibility in the Information Age. April 2013, 37–41.Koetsenruijter, A. W. M. (2011). Using numbers in news increases story credibility. Newspaper Research Journal, 32(2), 74–82. https://doi.org/10.1177/073953291103200207Lampos, V., Majumder, M. S., Yom-Tov, E., Edelstein, M., Moura, S., Hamada, Y., Rangaka, M. X., McKendry, R. A., & Cox, I. J. (2021). Tracking COVID-19 using online search. Npj Digital Medicine, 4(1), 1–11. https://doi.org/10.1038/s41746-021-00384-wLazer, D. M. J., Baum, M. A., Benkler, Y., Berinsky, A. J., Greenhill, K. M., Menczer, F., Metzger, M. J., Nyhan, B., Pennycook, G., Rothschild, D., Schudson, M., Sloman, S. A., Sunstein, C. R., Thorson, E. A., Watts, D. J., & Zittrain, J. L. (2018). The science of fake news. Science, 359(6380), 1094–1096. https://doi.org/10.1126/science.aao2998Lee, T. T. (2018). Virtual Theme Collection: “Trust and Credibility in News Media.” Journalism and Mass Communication Quarterly, 95(1), 23–27. https://doi.org/10.1177/1077699017749244McGrew, S., Breakstone, J., Ortega, T., Smith, M., & Wineburg, S. (2018). Can Students Evaluate Online Sources? Learning From Assessments of Civic Online Reasoning. Theory and Research in Social Education, 46(2), 165–193. https://doi.org/10.1080/00933104.2017.1416320Metzger, M. J., Flanagin, A. J., Eyal, K., Lemus, D. R., & Mccann, R. M. (2003). Credibility for the 21st Century: Integrating Perspectives on Source, Message, and Media Credibility in the Contemporary Media Environment. Annals of the International Communication Association, 27(1), 293–335. https://doi.org/10.1080/23808985.2003.11679029Meyer, H. K., & Thorson, D. M. (2010). The journalist behind the news: Credibility of straight, collaborative, opinionated, and blogged “news.” American Behavioral Scientist, 54(2), 100–119. https://doi.org/10.1177/0002764210376313Meyer, P. (1988). Defining and Measuring Credibility of Newspapers: Developing an Index. Journalism Quarterly, 65(3), 567–574. https://doi.org/10.1177/107769908806500301Nadi, S., Saraee, M. H., & Bagheri, A. (2011). A Hybrid Recommender System for Dynamic Web Users. International Journal of Multimedia and Image Processing, 1(1/2), 3–8. https://doi.org/10.20533/ijmip.2042.4647.2011.0001Newman, E. J., Garry, M., Bernstein, D. M., Kantner, J., & Lindsay, D. S. (2012). Nonprobative photographs (or words) inflate truthiness. Psychonomic Bulletin and Review, 19(5), 969–974. https://doi.org/10.3758/s13423-012-0292-0Olston, C., & Chi, E. H. (2003). ScentTrails: Integrating browsing and searching on the Web. ACM Transactions on Computer-Human Interaction, 10(3), 177–197. https://doi.org/10.1145/937549.937550Pehlivanoglu, D., Lin, T., Deceus, F., Heemskerk, A., Ebner, N. C., & Cahill, B. S. (2021). The role of analytical reasoning and source credibility on the evaluation of real and fake full-length news articles. Cognitive Research: Principles and Implications, 6(1). https://doi.org/10.1186/s41235-021-00292-3Pennycook, G., McPhetres, J., Zhang, Y., Lu, J. G., & Rand, D. G. (2020). Fighting COVID-19 Misinformation on Social Media: Experimental Evidence for a Scalable Accuracy-Nudge Intervention. Psychological Science, 31(7), 770–780. https://doi.org/10.1177/0956797620939054Pennycook, G., & Rand, D. G. (2019a). Fighting misinformation on social media using crowdsourced judgments of news source quality. Proceedings of the National Academy of Sciences of the United States of America, 116(7), 2521– 2526. https://doi.org/10.1073/pnas.1806781116Pennycook, G., & Rand, D. G. (2019b). Lazy, not biased: Susceptibility to partisan fake news is better explained by lack of reasoning than by motivated reasoning. Cognition, 188(June), 39–50. https://doi.org/10.1016/j.cognition.2018.06.011Preston, S., Anderson, A., Robertson, D. J., Shephard, M. P., & Huhe, N. (2021). Detecting fake news on Facebook: The role of emotional intelligence. PLoS ONE, 16(3 March), 1–13. https://doi.org/10.1371/journal.pone.0246757Ramachandran, M., & Chang, V. (2015). Recommendations and best practices for cloud enterprise security. Proceedings of the International Conference on Cloud Computing Technology and Science, CloudCom, 2015-Febru(February), 983– 988. https://doi.org/10.1109/CloudCom.2014.105Ranganathan, K., Ripeanu, M., Sarin, A., & Foster, I. (2003). To Share or Not to Share: An Analysis of Incentives to Contribute in Collaborative File-Sharing Environments. Proceedings of the Workshop on Economics of Peer to Peer Systems, 1–6.Rashkin, H., Choi, E., Jang, J. Y., Volkova, S., & Choi, Y. (2017). Truth of varying shades: Analyzing language in fake news and political fact-checking. EMNLP 2017 - Conference on Empirical Methods in Natural Language Processing, Proceedings, 2931–2937. https://doi.org/10.18653/v1/d17-1317Ross, R. M., Rand, D. G., & Pennycook, G. (2021). Beyond “fake news”: Analytic thinking and the detection of false and hyperpartisan news headlines. Judgment and Decision Making, 16(2), 484–504. https://doi.org/10.31234/osf.io/cgsx6Shenhav, A., Rand, D. G., & Greene, J. D. (2012). Divine intuition: Cognitive style influences belief in God. Journal of Experimental Psychology: General, 141(3), 423–428. https://doi.org/10.1037/a0025391Shu, K., Liu, H., Zhou, X., & Zafarani, R. (2018). Fake News: Fundamental Theories, Detection Strategies and Challenges. ArXiv, 836–837. https://doi.org/10.1007/978-3-319-94105-9_3Shu, K., Sliva, A., Wang, S., Tang, J., & Liu, H. (2017). Fake News Detection on Social Media: A Data Mining Perspective. CEUR Workshop Proceedings, 2041(1), 59–66.Stanovich, K. E., & West, R. F. (2000). "Individual differences in reasoning: Implications for the rationality debate? Behavioral and Brain Sciences, 26(4), 527. https://doi.org/10.1017/S0140525X03210116Steven A. Sloman. (1996). The Empirical Case for Two Systems of Reasoning. Psychological Bulletin, 119(1), 3–22.Tandoc, E. C., Lim, Z. W., & Ling, R. (2018). Defining “Fake News”: A typology of scholarly definitions. Digital Journalism, 6(2), 137–153. https://doi.org/10.1080/21670811.2017.1360143Toplak, M. E., West, R. F., & Stanovich, K. E. (2014). Assessing miserly information processing: An expansion of the Cognitive Reflection Test. Thinking and Reasoning, 20(2), 147–168. https://doi.org/10.1080/13546783.2013.844729Urban, J., & Schweiger, W. (2014). News Quality from the Recipients’ Perspective: Investigating recipients’ ability to judge the normative quality of news. Journalism Studies, 15(6), 821–840. https://doi.org/10.1080/1461670X.2013.856670Valenzuela, S., Piña, M., & Ramírez, J. (2017). Behavioral Effects of Framing on Social Media Users: How Conflict, Economic, Human Interest, and Morality Frames Drive News Sharing. Journal of Communication, 67(5), 803–826. https://doi.org/10.1111/jcom.12325Vereshchaka, A., Cosimini, S., & Dong, W. (2020). Analyzing and distinguishing fake and real news to mitigate the problem of disinformation. Computational and Mathematical Organization Theory, 26(3), 350–364. https://doi.org/10.1007/s10588-020-09307-8Vosoughi, S., Roy, D., & Aral, S. (2018). The spread of true and false news online. 1151(March), 1146–1151. https://news.1242.com/article/148290Wasserman, H., & Madrid-Morales, D. (2019). An Exploratory Study of “Fake News” and Media Trust in Kenya, Nigeria and South Africa. African Journalism Studies, 40(1), 107–123. https://doi.org/10.1080/23743670.2019.1627230Waszak, P. M., Kasprzycka-Waszak, W., & Kubanek, A. (2018). The spread of medical fake news in social media – The pilot quantitative study. Health Policy and Technology, 7(2), 115–118. https://doi.org/10.1016/j.hlpt.2018.03.002Watson, C. A. (2018). Information Literacy in a Fake/False News World: An Overview of the Characteristics of Fake News and its Historical Development. International Journal of Legal Information, 46(2), 93–96. https://doi.org/10.1017/jli.2018.25West, M. D. (1994). Validating a Scale for the Measurement of Credibility: A Covariance Structure Modeling Approach. Journalism Quarterly, 71(1), 159– 168. https://doi.org/10.1177/107769909407100115Zhou, X., & Zafarani, R. (2020). A Survey of Fake News: Fundamental Theories, Detection Methods, and Opportunities. ACM Computing Surveys, 53(5). https://doi.org/10.1145/3395046Zubiaga, A., & Ji, H. (2014). Tweet, but verify: epistemic study of information verification on Twitter. Social Network Analysis and Mining, 4(1), 1–12. https://doi.org/10.1007/s13278-014-0163-y吳志賢. (2005). 購物網站輔助系統設計之研究.呂珮瑜. (2015). 中文情緒詞庫的建造與標記.https://doi.org/10.6342/NTU201602978徐美苓. (2015). 影響新聞可信度與新聞素養效能因素之探討. Chinese Journal of Communication Research, 27, 99–136. 描述 碩士
國立政治大學
資訊管理學系
108356029資料來源 http://thesis.lib.nccu.edu.tw/record/#G0108356029 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 (Authors) 蘇晉威 zh_TW dc.contributor.author (Authors) Su, Jin-Wei en_US dc.creator (作者) 蘇晉威 zh_TW dc.creator (作者) Su, Jin-Wei en_US dc.date (日期) 2021 en_US dc.date.accessioned 2-Sep-2021 15:58:53 (UTC+8) - dc.date.available 2-Sep-2021 15:58:53 (UTC+8) - dc.date.issued (上傳時間) 2-Sep-2021 15:58:53 (UTC+8) - dc.identifier (Other Identifiers) G0108356029 en_US dc.identifier.uri (URI) http://nccur.lib.nccu.edu.tw/handle/140.119/136851 - 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) 108356029 zh_TW dc.description.abstract (摘要) 近年來,假新聞成為一個具有爭議性的議題,尤其在 2016 年美國總統大選期間和之後,人們對於此議題的重視更是與日俱增。並且由於社交媒體的普及,使得新思想的傳播更加便利,更加劇了其對民主、新聞環境和公眾信任的侵蝕。有鑑於假新聞議題的重要性,本研究將從受眾在閱讀新聞時的角度出發,試圖以一種網頁輔助系統新聞特徵標記的手段,協助受眾聚焦重要的新聞特徵,使其在遭遇假新聞時能降低其對該新聞的感知可信度。因此本研究將探討新聞網站進行假新聞特徵標記是否影響假新聞的感知可信度,並將認知反射測試的表現作為干擾變數,觀察其是否會干擾假新聞特徵標記與假新聞感知可信度之間的關聯。本研究使用問卷調查法在網路上發放問卷後,透過 SmartPLS 3 對回收之樣本以結構方程模式分析,並在確認研究之信度與效度後,對研究架構進行假說的檢定。研究結果發現假新聞特徵標記會負向顯著影響假新聞感知可信度,認知反射測試的干擾效果顯著。 zh_TW dc.description.tableofcontents 摘要 i第一章 緒論 1第一節 研究背景與動機 1第二節 研究目的 4第三節 研究流程 5第二章 文獻探討 6第一節 新聞的可信度及影響因素 6第二節 假新聞的特徵 9第三節 認知反思測試 12第四節 網頁輔助系統 15第三章 研究架構與方法 17第一節 研究架構 17第二節 研究假說 18第三節 研究方法 21第四節 實驗設計 25第四章 研究分析與成果 35第一節 資料收集與樣本結構分析35第二節 樣本檢驗與信效度分析39第三節 結構模型分析與假說檢定 42第四節 研究假設驗證結果 45第五章 研究結論與建議 46第一節 研究結果與討論 46第二節 研究貢獻與建議 48參考資料 50附錄一 正式實驗中兩情境之真新聞呈現 57附錄二 正式實驗中兩情境之假新聞呈現 58 zh_TW dc.format.extent 12015495 bytes - dc.format.mimetype application/pdf - dc.source.uri (資料來源) http://thesis.lib.nccu.edu.tw/record/#G0108356029 en_US dc.subject (關鍵詞) 假新聞特徵標記 zh_TW dc.subject (關鍵詞) 認知反思測試 zh_TW dc.subject (關鍵詞) 假新聞感知可信度 zh_TW dc.title (題名) 探討假新聞特徵標記及讀者認知風格對假新聞感知可信度之影響 zh_TW dc.title (題名) Exploring the Effect of Fake News Characteristic Markings on the Perceived Credibility of Readers with Different Cognitive Style in Fake News en_US dc.type (資料類型) thesis en_US dc.relation.reference (參考文獻) Adipat, B., Zhang, D., & Zhou, L. (2011). The effects of tree-view based presentation adaptation on mobile web browsing. MIS Quarterly: Management Information Systems, 35(1), 99–121. https://doi.org/10.2307/23043491Anderson, J. C., & Gerbing, D. W. (1988). Structural Equation Modeling in Practice: A Review and Recommended Two-Step Approach. Psychological Bulletin, 103(3), 411–423. https://doi.org/10.1037/0033-2909.103.3.411Appelman, A., & Sundar, S. S. (2016). Measuring message credibility: Construction and validation of an exclusive scale. Journalism and Mass Communication Quarterly, 93(1), 59–79. https://doi.org/10.1177/1077699015606057Apuke, O. D., & Omar, B. (2021). Fake news and COVID-19: modelling the predictors of fake news sharing among social media users. Telematics and Informatics, 56(March), 101475. https://doi.org/10.1016/j.tele.2020.101475Baum, J., & Abdel Rahman, R. (2021). Emotional news affects social judgments independent of perceived media credibility. Social Cognitive and Affective Neuroscience, 16(3), 280–291. https://doi.org/10.1093/scan/nsaa164Baum, J., Frömer, R., & Rahman, R. A. (2020). Fake news and metacognition : Emotional contents enhance confidence in social judgments based on untrustworthy headlines. 1–24.Berger, J., & Milkman, K. L. (2012). What makes online content viral? Journal of Marketing Research, 49(2), 192–205. https://doi.org/10.1509/jmr.10.0353Borah, P. (2014). The hyperlinked world: A look at how the interactions of news frames and hyperlinks influence news credibility and willingness to seek information. Journal of Computer-Mediated Communication, 19(3), 576–590. https://doi.org/10.1111/jcc4.12060Bright, J. (2016). The Social News Gap: How News Reading and News Sharing Diverge. Journal of Communication, 66(3), 343–365. https://doi.org/10.1111/jcom.12232Bronstein, M. V., Pennycook, G., Bear, A., Rand, D. G., & Cannon, T. D. (2019). Belief in Fake News is Associated with Delusionality, Dogmatism, Religious Fundamentalism, and Reduced Analytic Thinking. Journal of Applied Research in Memory and Cognition, 8(1), 108–117. https://doi.org/10.1016/j.jarmac.2018.09.005Cao, J., Qi, P., Sheng, Q., Yang, T., Guo, J., & Li, J. (2020). Exploring the role of visual content in fake news detection. ArXiv, 141–161. https://doi.org/10.1007/978-3-030-42699-6_8Cruz, A., Rocha, G., Sousa-Silva, R., & Lopes Cardoso, H. (2019). Team Fernando- Pessa at SemEval-2019 Task 4: Back to Basics in Hyperpartisan News Detection. 999–1003. https://doi.org/10.18653/v1/s19-2173Duffy, A., Tandoc, E., & Ling, R. (2020). Too good to be true, too good not to share: the social utility of fake news. Information Communication and Society, 23(13), 1965–1979. https://doi.org/10.1080/1369118X.2019.1623904Dufrasne, M., Mercenier, H., & Wiard, V. (2020). Teens, social media and fake news: A user’s perspective.Epstein, S. (1994). Integration of the Cognitive and the Psychodynamic Unconscious. American Psychologist, 49(8), 709–724. https://doi.org/10.1037//0003- 066x.49.8.709Fornell, C., & Larcker, D. F. (1981). Fornell, C. and Larcker, D.F. (1981), “Evaluating structural equation models with unobservable variables and.pdf. Journal of Marketing Research, XVIII(February), 39–50.Frederick, S. (2005). Cognitive reflection and decision making. Journal of Economic Perspectives, 19(4), 25–42. https://doi.org/10.1257/089533005775196732Gao, G., Wang, H. C., Cosley, D., & Fussell, S. R. (2013). Same translation but different experience: The effects of highlighting on machine - Translated conversations. Conference on Human Factors in Computing Systems - Proceedings, 449–458. https://doi.org/10.1145/2470654.2470719Gaozhao, D. (2021). Flagging fake news on social media: An experimental study of media consumers’ identification of fake news. Government Information Quarterly, 38(March). https://doi.org/10.1016/j.giq.2021.101591Golbeck, J., Mauriello, M., Auxier, B., Bhanushali, K. H., Bonk, C., Bouzaghrane, M. A., Buntain, C., Chanduka, R., Cheakalos, P., Everett, J. B., Falak, W., Gieringer, C., Graney, J., Hoffman, K. M., Huth, L., Ma, Z., Jha, M., Khan, M., Kori, V., ... Visnansky, G. (2018). Fake news vs satire: A dataset and analysis. WebSci 2018 - Proceedings of the 10th ACM Conference on Web Science, 17– 21. https://doi.org/10.1145/3201064.3201100Gu, L., Kropotov, V., & Yarochkin, F. (2017). How Propagandists Abuse the Internet and Manipulate the Public. Trend Micro, 5, 1–81. https://documents.trendmicro.com/assets/white_papers/wp-fake-news-machine- how-propagandists-abuse-the-internet.pdfGunawan, F. E., & Suwandi, V. (2020). Identifying the most influencing characteristics of fake news. ICIC Express Letters, Part B: Applications, 11(1), 93–101. https://doi.org/10.24507/icicelb.11.01.93Haigh, M., Haigh, T., & Kozak, N. I. (2018). Stopping Fake News: The work practices of peer-to-peer counter propaganda. Journalism Studies, 19(14), 2062– 2087. https://doi.org/10.1080/1461670X.2017.1316681Horne, B. D., & Adalı, S. (2017). This just in: Fake news packs a lot in title, uses simpler, repetitive content in text body, more similar to satire than real news. ArXiv, 759–766.Hou, Z., Du, F., Jiang, H., Zhou, X., Lin, L., Assessment, T., & Commission, N. H. (2020). Assessment of public attention, risk perception, emotional and behavioural responses to the COVID-19 outbreak: social media surveillance in China.Huynh TL. (2020). The COVID-19 risk perception: A survey on socioeconomics and media attention. Economics Bulletin. . AccessEcon, 40(1(1), 758–764.Johnson, B. K. A., & Wiedenbeck, S. (2009). Perceived credibility of citizen journalism. Journalism & Mass Communication Quarterly, 82"(2), 332–348. http://jmq.sagepub.com.eresources.shef.ac.uk/content/86/2/332.full.pdf+htmlJones-Jang, S. M., Mortensen, T., & Liu, J. (2021). Does Media Literacy Help Identification of Fake News? Information Literacy Helps, but Other Literacies Don’t. American Behavioral Scientist, 65(2), 371–388. https://doi.org/10.1177/0002764219869406Juanchich, M., Dewberry, C., Sirota, M., & Narendran, S. (2016). Cognitive Reflection Predicts Real-Life Decision Outcomes, but Not Over and Above Personality and Decision-Making Styles. Journal of Behavioral Decision Making, 29(1), 52–59. https://doi.org/10.1002/bdm.1875Jungnickel, K. (2011). Nachrichtenqualität aus Nutzersicht. Medien & Kommunikationswissenschaft, 59(3), 360–378.Kahneman, D., & Frederick, S. (2012). Representativeness Revisited: Attribute Substitution in Intuitive Judgment. In Heuristics and Biases (Issue July 2002). https://doi.org/10.1017/cbo9780511808098.004Kanoh, H. (2018). Why do people believe in fake news over the Internet? Why do people believe in fake news over the Internet? An understanding from the perspective of existence of the habit of An understanding from the perspective of existence of the habit of eating and dr.Karlsson, M., & Clerwall, C. (2018). Transparency to the Rescue?: Evaluating citizens’ views on transparency tools in journalism. Journalism Studies, 19(13), 1923–1933. https://doi.org/10.1080/1461670X.2018.1492882Kim, H. S. (2015). Attracting Views and Going Viral: How Message Features and News-Sharing Channels Affect Health News Diffusion. Journal of Communication, 65(3), 512–534. https://doi.org/10.1111/jcom.12160Kiousis, S. (2001). Public Trust or Mistrust ? Perceptions of Media Credibility in the Information Age Public Trust or Mistrust ? Perceptions of Media Credibility in the Information Age. April 2013, 37–41.Koetsenruijter, A. W. M. (2011). Using numbers in news increases story credibility. Newspaper Research Journal, 32(2), 74–82. https://doi.org/10.1177/073953291103200207Lampos, V., Majumder, M. S., Yom-Tov, E., Edelstein, M., Moura, S., Hamada, Y., Rangaka, M. X., McKendry, R. A., & Cox, I. J. (2021). Tracking COVID-19 using online search. Npj Digital Medicine, 4(1), 1–11. https://doi.org/10.1038/s41746-021-00384-wLazer, D. M. J., Baum, M. A., Benkler, Y., Berinsky, A. J., Greenhill, K. M., Menczer, F., Metzger, M. J., Nyhan, B., Pennycook, G., Rothschild, D., Schudson, M., Sloman, S. A., Sunstein, C. R., Thorson, E. A., Watts, D. J., & Zittrain, J. L. (2018). The science of fake news. Science, 359(6380), 1094–1096. https://doi.org/10.1126/science.aao2998Lee, T. T. (2018). Virtual Theme Collection: “Trust and Credibility in News Media.” Journalism and Mass Communication Quarterly, 95(1), 23–27. https://doi.org/10.1177/1077699017749244McGrew, S., Breakstone, J., Ortega, T., Smith, M., & Wineburg, S. (2018). Can Students Evaluate Online Sources? Learning From Assessments of Civic Online Reasoning. Theory and Research in Social Education, 46(2), 165–193. https://doi.org/10.1080/00933104.2017.1416320Metzger, M. J., Flanagin, A. J., Eyal, K., Lemus, D. R., & Mccann, R. M. (2003). Credibility for the 21st Century: Integrating Perspectives on Source, Message, and Media Credibility in the Contemporary Media Environment. Annals of the International Communication Association, 27(1), 293–335. https://doi.org/10.1080/23808985.2003.11679029Meyer, H. K., & Thorson, D. M. (2010). The journalist behind the news: Credibility of straight, collaborative, opinionated, and blogged “news.” American Behavioral Scientist, 54(2), 100–119. https://doi.org/10.1177/0002764210376313Meyer, P. (1988). Defining and Measuring Credibility of Newspapers: Developing an Index. Journalism Quarterly, 65(3), 567–574. https://doi.org/10.1177/107769908806500301Nadi, S., Saraee, M. H., & Bagheri, A. (2011). A Hybrid Recommender System for Dynamic Web Users. International Journal of Multimedia and Image Processing, 1(1/2), 3–8. https://doi.org/10.20533/ijmip.2042.4647.2011.0001Newman, E. J., Garry, M., Bernstein, D. M., Kantner, J., & Lindsay, D. S. (2012). Nonprobative photographs (or words) inflate truthiness. Psychonomic Bulletin and Review, 19(5), 969–974. https://doi.org/10.3758/s13423-012-0292-0Olston, C., & Chi, E. H. (2003). ScentTrails: Integrating browsing and searching on the Web. ACM Transactions on Computer-Human Interaction, 10(3), 177–197. https://doi.org/10.1145/937549.937550Pehlivanoglu, D., Lin, T., Deceus, F., Heemskerk, A., Ebner, N. C., & Cahill, B. S. (2021). The role of analytical reasoning and source credibility on the evaluation of real and fake full-length news articles. Cognitive Research: Principles and Implications, 6(1). https://doi.org/10.1186/s41235-021-00292-3Pennycook, G., McPhetres, J., Zhang, Y., Lu, J. G., & Rand, D. G. (2020). Fighting COVID-19 Misinformation on Social Media: Experimental Evidence for a Scalable Accuracy-Nudge Intervention. Psychological Science, 31(7), 770–780. https://doi.org/10.1177/0956797620939054Pennycook, G., & Rand, D. G. (2019a). Fighting misinformation on social media using crowdsourced judgments of news source quality. Proceedings of the National Academy of Sciences of the United States of America, 116(7), 2521– 2526. https://doi.org/10.1073/pnas.1806781116Pennycook, G., & Rand, D. G. (2019b). Lazy, not biased: Susceptibility to partisan fake news is better explained by lack of reasoning than by motivated reasoning. Cognition, 188(June), 39–50. https://doi.org/10.1016/j.cognition.2018.06.011Preston, S., Anderson, A., Robertson, D. J., Shephard, M. P., & Huhe, N. (2021). Detecting fake news on Facebook: The role of emotional intelligence. PLoS ONE, 16(3 March), 1–13. https://doi.org/10.1371/journal.pone.0246757Ramachandran, M., & Chang, V. (2015). Recommendations and best practices for cloud enterprise security. Proceedings of the International Conference on Cloud Computing Technology and Science, CloudCom, 2015-Febru(February), 983– 988. https://doi.org/10.1109/CloudCom.2014.105Ranganathan, K., Ripeanu, M., Sarin, A., & Foster, I. (2003). To Share or Not to Share: An Analysis of Incentives to Contribute in Collaborative File-Sharing Environments. Proceedings of the Workshop on Economics of Peer to Peer Systems, 1–6.Rashkin, H., Choi, E., Jang, J. Y., Volkova, S., & Choi, Y. (2017). Truth of varying shades: Analyzing language in fake news and political fact-checking. EMNLP 2017 - Conference on Empirical Methods in Natural Language Processing, Proceedings, 2931–2937. https://doi.org/10.18653/v1/d17-1317Ross, R. M., Rand, D. G., & Pennycook, G. (2021). Beyond “fake news”: Analytic thinking and the detection of false and hyperpartisan news headlines. Judgment and Decision Making, 16(2), 484–504. https://doi.org/10.31234/osf.io/cgsx6Shenhav, A., Rand, D. G., & Greene, J. D. (2012). Divine intuition: Cognitive style influences belief in God. Journal of Experimental Psychology: General, 141(3), 423–428. https://doi.org/10.1037/a0025391Shu, K., Liu, H., Zhou, X., & Zafarani, R. (2018). Fake News: Fundamental Theories, Detection Strategies and Challenges. ArXiv, 836–837. https://doi.org/10.1007/978-3-319-94105-9_3Shu, K., Sliva, A., Wang, S., Tang, J., & Liu, H. (2017). Fake News Detection on Social Media: A Data Mining Perspective. CEUR Workshop Proceedings, 2041(1), 59–66.Stanovich, K. E., & West, R. F. (2000). "Individual differences in reasoning: Implications for the rationality debate? Behavioral and Brain Sciences, 26(4), 527. https://doi.org/10.1017/S0140525X03210116Steven A. Sloman. (1996). The Empirical Case for Two Systems of Reasoning. Psychological Bulletin, 119(1), 3–22.Tandoc, E. C., Lim, Z. W., & Ling, R. (2018). Defining “Fake News”: A typology of scholarly definitions. Digital Journalism, 6(2), 137–153. https://doi.org/10.1080/21670811.2017.1360143Toplak, M. E., West, R. F., & Stanovich, K. E. (2014). Assessing miserly information processing: An expansion of the Cognitive Reflection Test. Thinking and Reasoning, 20(2), 147–168. https://doi.org/10.1080/13546783.2013.844729Urban, J., & Schweiger, W. (2014). News Quality from the Recipients’ Perspective: Investigating recipients’ ability to judge the normative quality of news. Journalism Studies, 15(6), 821–840. https://doi.org/10.1080/1461670X.2013.856670Valenzuela, S., Piña, M., & Ramírez, J. (2017). Behavioral Effects of Framing on Social Media Users: How Conflict, Economic, Human Interest, and Morality Frames Drive News Sharing. Journal of Communication, 67(5), 803–826. https://doi.org/10.1111/jcom.12325Vereshchaka, A., Cosimini, S., & Dong, W. (2020). Analyzing and distinguishing fake and real news to mitigate the problem of disinformation. Computational and Mathematical Organization Theory, 26(3), 350–364. https://doi.org/10.1007/s10588-020-09307-8Vosoughi, S., Roy, D., & Aral, S. (2018). The spread of true and false news online. 1151(March), 1146–1151. https://news.1242.com/article/148290Wasserman, H., & Madrid-Morales, D. (2019). An Exploratory Study of “Fake News” and Media Trust in Kenya, Nigeria and South Africa. African Journalism Studies, 40(1), 107–123. https://doi.org/10.1080/23743670.2019.1627230Waszak, P. M., Kasprzycka-Waszak, W., & Kubanek, A. (2018). The spread of medical fake news in social media – The pilot quantitative study. Health Policy and Technology, 7(2), 115–118. https://doi.org/10.1016/j.hlpt.2018.03.002Watson, C. A. (2018). Information Literacy in a Fake/False News World: An Overview of the Characteristics of Fake News and its Historical Development. International Journal of Legal Information, 46(2), 93–96. https://doi.org/10.1017/jli.2018.25West, M. D. (1994). Validating a Scale for the Measurement of Credibility: A Covariance Structure Modeling Approach. Journalism Quarterly, 71(1), 159– 168. https://doi.org/10.1177/107769909407100115Zhou, X., & Zafarani, R. (2020). A Survey of Fake News: Fundamental Theories, Detection Methods, and Opportunities. ACM Computing Surveys, 53(5). https://doi.org/10.1145/3395046Zubiaga, A., & Ji, H. (2014). Tweet, but verify: epistemic study of information verification on Twitter. Social Network Analysis and Mining, 4(1), 1–12. https://doi.org/10.1007/s13278-014-0163-y吳志賢. (2005). 購物網站輔助系統設計之研究.呂珮瑜. (2015). 中文情緒詞庫的建造與標記.https://doi.org/10.6342/NTU201602978徐美苓. (2015). 影響新聞可信度與新聞素養效能因素之探討. Chinese Journal of Communication Research, 27, 99–136. zh_TW dc.identifier.doi (DOI) 10.6814/NCCU202101355 en_US