學術產出-學位論文

文章檢視/開啟

書目匯出

Google ScholarTM

政大圖書館

引文資訊

TAIR相關學術產出

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 2-九月-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/10.2307/23043491
Anderson, 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/10.1037/0033-2909.103.3.411
Appelman, 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/10.1177/1077699015606057
Apuke, 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.2020.101475
Baum, 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/nsaa164
Baum, 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.10.0353
Borah, 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/jcc4.12060
Bright, 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.12232
Bronstein, 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.2018.09.005
Cao, 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_8
Cruz, 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/s19-2173
Duffy, 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.2019.1623904
Dufrasne, 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.49.8.709
Fornell, 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/10.1257/089533005775196732
Gao, 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/10.1145/2470654.2470719
Gaozhao, 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.2021.101591
Golbeck, 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/10.1145/3201064.3201100
Gu, 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.pdf
Gunawan, 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.11.01.93
Haigh, 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.2017.1316681
Horne, 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+html
Jones-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/10.1177/0002764219869406
Juanchich, 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.1875
Jungnickel, 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/cbo9780511808098.004
Kanoh, 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.2018.1492882
Kim, 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.12160
Kiousis, 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/10.1177/073953291103200207
Lampos, 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-w
Lazer, 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.aao2998
Lee, T. T. (2018). Virtual Theme Collection: “Trust and Credibility in News Media.” Journalism and Mass Communication Quarterly, 95(1), 23–27. https://doi.org/10.1177/1077699017749244
McGrew, 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/10.1080/00933104.2017.1416320
Metzger, 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/10.1080/23808985.2003.11679029
Meyer, 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/10.1177/0002764210376313
Meyer, P. (1988). Defining and Measuring Credibility of Newspapers: Developing an Index. Journalism Quarterly, 65(3), 567–574. https://doi.org/10.1177/107769908806500301
Nadi, 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.2042.4647.2011.0001
Newman, 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/s13423-012-0292-0
Olston, 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/10.1145/937549.937550
Pehlivanoglu, 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/s41235-021-00292-3
Pennycook, 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/10.1177/0956797620939054
Pennycook, 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.1806781116
Pennycook, 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.2018.06.011
Preston, 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.0246757
Ramachandran, 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.2014.105
Ranganathan, 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/d17-1317
Ross, 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/cgsx6
Shenhav, 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/a0025391
Shu, 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_3
Shu, 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/S0140525X03210116
Steven 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/10.1080/21670811.2017.1360143
Toplak, 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/10.1080/13546783.2013.844729
Urban, 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.2013.856670
Valenzuela, 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.12325
Vereshchaka, 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/s10588-020-09307-8
Vosoughi, S., Roy, D., & Aral, S. (2018). The spread of true and false news online. 1151(March), 1146–1151. https://news.1242.com/article/148290
Wasserman, 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/10.1080/23743670.2019.1627230
Waszak, 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.2018.03.002
Watson, 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.2018.25
West, 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/10.1177/107769909407100115
Zhou, X., & Zafarani, R. (2020). A Survey of Fake News: Fundamental Theories, Detection Methods, and Opportunities. ACM Computing Surveys, 53(5). https://doi.org/10.1145/3395046
Zubiaga, 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-Hungen_US
dc.contributor.author (作者) 蘇晉威zh_TW
dc.contributor.author (作者) Su, Jin-Weien_US
dc.creator (作者) 蘇晉威zh_TW
dc.creator (作者) Su, Jin-Weien_US
dc.date (日期) 2021en_US
dc.date.accessioned 2-九月-2021 15:58:53 (UTC+8)-
dc.date.available 2-九月-2021 15:58:53 (UTC+8)-
dc.date.issued (上傳時間) 2-九月-2021 15:58:53 (UTC+8)-
dc.identifier (其他 識別碼) G0108356029en_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) 108356029zh_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/#G0108356029en_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 Newsen_US
dc.type (資料類型) thesisen_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/10.2307/23043491
Anderson, 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/10.1037/0033-2909.103.3.411
Appelman, 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/10.1177/1077699015606057
Apuke, 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.2020.101475
Baum, 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/nsaa164
Baum, 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.10.0353
Borah, 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/jcc4.12060
Bright, 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.12232
Bronstein, 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.2018.09.005
Cao, 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_8
Cruz, 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/s19-2173
Duffy, 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.2019.1623904
Dufrasne, 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.49.8.709
Fornell, 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/10.1257/089533005775196732
Gao, 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/10.1145/2470654.2470719
Gaozhao, 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.2021.101591
Golbeck, 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/10.1145/3201064.3201100
Gu, 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.pdf
Gunawan, 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.11.01.93
Haigh, 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.2017.1316681
Horne, 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+html
Jones-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/10.1177/0002764219869406
Juanchich, 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.1875
Jungnickel, 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/cbo9780511808098.004
Kanoh, 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.2018.1492882
Kim, 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.12160
Kiousis, 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/10.1177/073953291103200207
Lampos, 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-w
Lazer, 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.aao2998
Lee, T. T. (2018). Virtual Theme Collection: “Trust and Credibility in News Media.” Journalism and Mass Communication Quarterly, 95(1), 23–27. https://doi.org/10.1177/1077699017749244
McGrew, 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/10.1080/00933104.2017.1416320
Metzger, 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/10.1080/23808985.2003.11679029
Meyer, 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/10.1177/0002764210376313
Meyer, P. (1988). Defining and Measuring Credibility of Newspapers: Developing an Index. Journalism Quarterly, 65(3), 567–574. https://doi.org/10.1177/107769908806500301
Nadi, 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.2042.4647.2011.0001
Newman, 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/s13423-012-0292-0
Olston, 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/10.1145/937549.937550
Pehlivanoglu, 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/s41235-021-00292-3
Pennycook, 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/10.1177/0956797620939054
Pennycook, 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.1806781116
Pennycook, 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.2018.06.011
Preston, 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.0246757
Ramachandran, 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.2014.105
Ranganathan, 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/d17-1317
Ross, 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/cgsx6
Shenhav, 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/a0025391
Shu, 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_3
Shu, 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/S0140525X03210116
Steven 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/10.1080/21670811.2017.1360143
Toplak, 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/10.1080/13546783.2013.844729
Urban, 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.2013.856670
Valenzuela, 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.12325
Vereshchaka, 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/s10588-020-09307-8
Vosoughi, S., Roy, D., & Aral, S. (2018). The spread of true and false news online. 1151(March), 1146–1151. https://news.1242.com/article/148290
Wasserman, 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/10.1080/23743670.2019.1627230
Waszak, 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.2018.03.002
Watson, 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.2018.25
West, 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/10.1177/107769909407100115
Zhou, X., & Zafarani, R. (2020). A Survey of Fake News: Fundamental Theories, Detection Methods, and Opportunities. ACM Computing Surveys, 53(5). https://doi.org/10.1145/3395046
Zubiaga, 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/NCCU202101355en_US