政大機構典藏-National Chengchi University Institutional Repository(NCCUR):Item 140.119/141043
English  |  正體中文  |  简体中文  |  Post-Print筆數 : 27 |  Items with full text/Total items : 113324/144300 (79%)
Visitors : 51152267      Online Users : 872
RC Version 6.0 © Powered By DSPACE, MIT. Enhanced by NTU Library IR team.
Scope Tips:
  • please add "double quotation mark" for query phrases to get precise results
  • please goto advance search for comprehansive author search
    •  Adv. Search
    Home ‧ Login ‧ Upload ‧ Help ‧ About ‧ Administer Goto mobile version
    政大典藏 > College of Commerce > Department of MIS > Theses >  Item 140.119/141043


    Please use this identifier to cite or link to this item: https://nccur.lib.nccu.edu.tw/handle/140.119/141043


    Title: 探討假新聞特徵摘要輔助系統及觀點取替對假新聞感知可信度之影響
    Exploring the Effect of Fake News Characteristic Summarization Support System on the Perceived Credibility of Readers with Different Perspective Taking in Fake News
    Authors: 胡祐銓
    Hu, Yu-Chuan
    Contributors: 彭志宏
    Peng, Chih-Hung
    胡祐銓
    Hu, Yu-Chuan
    Keywords: 假新聞特徵摘要
    假新聞感知可信度
    觀點取替
    Fake News Features Summaries
    Perspective Taking
    Perceived Credibility Of Fake News
    Date: 2022
    Issue Date: 2022-08-01 17:24:56 (UTC+8)
    Abstract: 近年來假新聞數量激增，也有越來越多相關研究幫助人們遏止假新聞危
    害。本研究提出一種網頁輔助系統，在新聞網站中，透過彙整假新聞特徵的摘要的方式提供人們快速掌握假新聞特徵，希望能降低人們對於假新聞的感知可信度。也希望瞭解人們面對假新聞時的心理操弄是否會影響輔助系統的幫助，因此透過觀點取替的動作，了解人們在面對假新聞時能否透過站在自己或他人的角度與立場思考，使人們激發不一樣的思考邏輯，最終調節人們在有無使用輔助系統的狀態中，對於假新聞感知可信度的影響。

    本研究透過開發新聞網站系統，並使用問卷調查法發放網路問卷，接著使用SPSS 進行分析，在確認信度與效度以及實驗操弄有效後，進行研究的假說檢定。最終發現假新聞特徵摘要能夠顯著的負向影響假新聞的新聞感知可信度。也發現人們進行觀點取替站在自己立場角度思考時，有假新聞特徵摘要輔助系統的情況比起沒有的情況，可以顯著的更降低假新聞的感知可信度，而人們進行觀點取替站在他人角度思考時，有無假新聞特徵摘要輔助系統的幫助則不會對假新聞的感知可信度產生顯著影響。
    The fake news significantly affects people’s daily lives. Prior research focuses on how to design different technologies/algorithms to evaluate fake news. However, little is known how a web support system can help people evaluate fake news and how perspective taking plays a role in fake news evaluation. Therefore, this study purposes
    a web system which incorporates and summarizes fake news features.

    To examine our hypotheses, we conduct an online experiment. We find that the fake news feature summarization support system decreases the perceived credibility of
    fake news and that the perspective taking moderates this relationship. Our findings have critical theoretical and practical contributions.
    Reference: 1. Abdi, A., Idris, N., Alguliyev, R. M., & Aliguliyev, R. M. (2016). An automated summarization assessment algorithm for identifying summarizing strategies. PloS one, 11(1), e0145809.
    2. Adipat, B., Zhang, D., & Zhou, L. (2011). The effects of tree-view based presentation adaptation on mobile web browsing. MIS quarterly, 99-121.
    3. Alguliyev, R. M., Aliguliyev, R. M., Isazade, N. R., Abdi, A., & Idris, N. (2019). COSUM: Text summarization based on clustering and optimization. Expert Systems, 36(1), e12340.
    4. Allcott, H., & Gentzkow, M. (2017). Social media and fake news in the 2016 election. Journal of economic perspectives, 31(2), 211-236.
    5. 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, 101475.
    6. Au, C. H., Ho, K. K., & Chiu, D. K. (2021). The role of online misinformation and fake news in ideological polarization: barriers, catalysts, and implications. Information Systems Frontiers, 1-24.
    7. Badrinarayanan, V., Becerra, E. P., Kim, C.-H., & Madhavaram, S. (2012). Transference and congruence effects on purchase intentions in online stores of multi-channel retailers: initial evidence from the US and South Korea. Journal of the Academy of Marketing Science, 40(4), 539-557.
    8. Balakrishnan, V., & Norman, A.-A. (2020). Psychological motives of cyberbullying among Malaysian young adults. Asia Pacific Journal of Social Work and Development, 30(3), 181-194.
    9. Bang, Y., Ishii, E., Cahyawijaya, S., Ji, Z., & Fung, P. (2021). Model generalization on covid-19 fake news detection. Paper presented at the International Workshop on Combating On line Ho st ile Posts in Regional Languages dur ing Emerge ncy Si tuation.
    10. Batson, C. D. (2011). Altruism in humans: Oxford University Press, USA.
    11. Batson, C. D. (2014). The altruism question: Toward a social-psychological answer: Psychology Press.
    12. 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.
    13. Bechwati, N. N., & Xia, L. (2003). Do computers sweat? The impact of perceived effort of online decision aids on consumers’ satisfaction with the decision process. Journal of Consumer Psychology, 13(1-2), 139-148.
    14. Beer, D. d., & Matthee, M. (2020). Approaches to identify fake news: A systematic literature review. Paper presented at the International Conference on Integrated Science.
    15. Bellman, S., & Rossiter, J. R. (2004). The website schema. Journal of Interactive Advertising, 4(2), 38-48.
    16. Bhushan, D., Agrawal, C., & Yadav, H. (2019). Fake News Detection: Tools, Techniques, and Methodologies. Paper presented at the International Conference on Information Management & Machine Intelligence.
    17. Booth, D. (2004). The Human-Computer Interaction Handbook: Fundamentals Evolving Technologies and Emerging Applications. Journal of Occupational Psychology, Employment and Disability, 6(2), 85-87.
    18. 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.
    19. Brunyé, T. T., Ditman, T., Mahoney, C. R., Augustyn, J. S., & Taylor, H. A. (2009). When you and I share perspectives: Pronouns modulate perspective taking during narrative comprehension. Psychological Science, 20(1), 27-32.
    20. Bryanov, K., & Vziatysheva, V. (2021). Determinants of individuals’ belief in fake news: A scoping review determinants of belief in fake news. PloS one, 16(6), e0253717.
    21. Bryman, A., & Cramer, D. (1999). Quantitative data analysis with SPSS release 8 for Windows: a guide for social scientists: Taylor & Francis US.
    22. Bucy, E. P. (2003). Media credibility reconsidered: Synergy effects between on-air and online news. Journalism & Mass Communication Quarterly, 80(2), 247-264.
    23. Burkhardt, J. M. (2017). History of fake news. Library Technology Reports, 53(8), 5-9.
    24. Campbell, W. J. (2001). Yellow journalism: Puncturing the myths, defining the legacies: Greenwood Publishing Group.
    25. Cao, J., Qi, P., Sheng, Q., Yang, T., Guo, J., & Li, J. (2020). Exploring the role of visual content in fake news detection. Disinformation, Misinformation, and Fake News in Social Media, 141-161.
    26. Castillo, C., Mendoza, M., & Poblete, B. (2011). Information credibility on twitter. Paper presented at the Proceedings of the 20th international conference on World wide web.
    27. Chadwick-Dias, A., Tedesco, D., & Tullis, T. (2004). Demographic differences in preferred web site content. Paper presented at the Proceedings of Usability Professionals` Association Annual Conference, Minnesota.
    28. Chen, J. V., Le, H. T., & Tran, S. T. T. (2021). Understanding automated conversational agent as a decision aid: matching agent`s conversation with customer`s shopping task. Internet Research.
    29. Chen, R., & Sakamoto, Y. (2013). Perspective matters: Sharing of crisis information in social media. Paper presented at the 2013 46th Hawaii international conference on system sciences.
    30. Cheung, C. M.-Y., Sia, C.-L., & Kuan, K. K. (2012). Is this review believable? A study of factors affecting the credibility of online consumer reviews from an ELM perspective. Journal of the Association for Information Systems, 13(8), 2.
    31. Chuai, Y., & Zhao, J. (2020). Anger makes fake news viral online. arXiv preprint arXiv:2004.10399.
    32. Chung, C. J., Nam, Y., & Stefanone, M. A. (2012). Exploring online news credibility: The relative influence of traditional and technological factors. Journal of computer-mediated communication, 17(2), 171-186.
    33. Chung, H. (2016). PSYCHOLOGICAL EGOISM AND HOBBES. Filozofia, 71(3).
    34. Coke, J. S., Batson, C. D., & McDavis, K. (1978). Empathic mediation of helping: a two-stage model. Journal of personality and social psychology, 36(7), 752.
    35. Cook, J., Van Der Linden, S., Lewandowsky, S., & Ecker, U. K. (2020). Coronavirus,‘Plandemic’and the seven traits of conspiratorial thinking.
    36. Cooley, D., & Parks-Yancy, R. (2019). The effect of social media on perceived information credibility and decision making. Journal of Internet Commerce, 18(3), 249-269.
    37. Davis, M. H. (1983). Measuring individual differences in empathy: evidence for a multidimensional approach. Journal of personality and social psychology, 44(1), 113.
    38. Davis, M. H., Conklin, L., Smith, A., & Luce, C. (1996). Effect of perspective taking on the cognitive representation of persons: a merging of self and other. Journal of personality and social psychology, 70(4), 713.
    39. Davis, W. (2016). Fake or real? How to self-check the news and get the facts. NPR: All Tech Considered.
    40. Devitt, A., & Ahmad, K. (2007). Sentiment polarity identification in financial news: A cohesion-based approach. Paper presented at the Proceedings of the 45th annual meeting of the association of computational linguistics.
    41. 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 & Society, 23(13), 1965-1979.
    42. Emrich, O., & Verhoef, P. C. (2015). The impact of a homogenous versus a prototypical Web design on online retail patronage for multichannel providers. International Journal of Research in Marketing, 32(4), 363-374.
    43. Epley, N., Caruso, E. M., & Bazerman, M. H. (2006). When perspective taking increases taking: reactive egoism in social interaction. Journal of personality and social psychology, 91(5), 872.
    44. Fernández-López, M., & Perea, M. (2020). Language does not modulate fake news credibility, but emotion does. Psicológica Journal, 41(2), 84-102.
    45. Fogg, B. J. (2003). Prominence-interpretation theory: Explaining how people assess credibility online. Paper presented at the CHI`03 extended abstracts on human factors in computing systems.
    46. Frank, R. (2018). Fake News vs.“Foke” News: A Brief, Personal, Recent History. Journal of American Folklore, 131(522), 379-387.
    47. Galinsky, A. D., & Ku, G. (2004). The effects of perspective-taking on prejudice: The moderating role of self-evaluation. Personality and social psychology bulletin, 30(5), 594-604.
    48. Galinsky, A. D., Ku, G., & Wang, C. S. (2005). Perspective-taking and self-other overlap: Fostering social bonds and facilitating social coordination. Group processes & intergroup relations, 8(2), 109-124.
    49. Galinsky, A. D., & Moskowitz, G. B. (2000). Perspective-taking: decreasing stereotype expression, stereotype accessibility, and in-group favoritism. Journal of personality and social psychology, 78(4), 708.
    50. Gambhir, M., & Gupta, V. (2017). Recent automatic text summarization techniques: a survey. Artificial Intelligence Review, 47(1), 1-66.
    51. Gaozhao, D. (2021). Flagging fake news on social media: An experimental study of media consumers` identification of fake news. Government Information Quarterly, 38(3), 101591.
    52. Ghanem, B., Rosso, P., & Rangel, F. (2020). An emotional analysis of false information in social media and news articles. ACM Transactions on Internet Technology (TOIT), 20(2), 1-18.
    53. Gorenflo, D. W., & Crano, W. D. (1998). The multiple perspectives inventory: A measure of perspective-taking. Swiss journal of psychology, 57(3), 163-177.
    54. Gould, J. R., & Coyle, S. J. (2002). How consumers generate clickstreams through web sites: An empirical investigation of hypertext, schema and mapping theoretical explanations. Journal of Interactive Advertising, 2(2), 42-56.
    55. Gunawan, F., & Suwandi, V. (2020). Identifying the most influencing characteristics of fake news. ICIC Express Lett. Part B: Appl., 11(1), 93-101.
    56. Heyneman, S. P. (2021). Fake news, fake truth: A new purpose for public schooling. International Journal of Educational Development, 87, 102496.
    57. Hindman, M. (2018). Disinformation, fake news and influence campaigns on Twitter: John S. and James L. Knight Foundation.
    58. Häubl, G., & Trifts, V. (2000). Consumer decision making in online shopping environments: The effects of interactive decision aids. Marketing science, 19(1), 4-21.
    59. Hovland, C. I., Janis, I. L., & Kelley, H. H. (1953). Communication and persuasion.
    60. Howard, P. N., Kollanyi, B., Bradshaw, S., & Neudert, L.-M. (2018). Social media, news and political information during the US election: Was polarizing content concentrated in swing states? arXiv preprint arXiv:1802.03573.
    61. Howe, P., & Teufel, B. (2014). Native advertising and digital natives: The effects of age and advertisement format on news website credibility judgments. ISOJ Journal, 4(1), 78-90.
    62. Jack, C. (2017). Lexicon of lies: Terms for problematic information. Data & Society, 3(22), 1094-1096.
    63. Jang, S. M., & Kim, J. K. (2018). Third person effects of fake news: Fake news regulation and media literacy interventions. Computers in Human Behavior, 80, 295-302.
    64. Johnson, K. A., & Wiedenbeck, S. (2009). Enhancing perceived credibility of citizen journalism web sites. Journalism & Mass Communication Quarterly, 86(2), 332-348.
    65. Kalsnes, B. (2018). Fake news Oxford Research Encyclopedia of Communication.
    66. Kim, G., & Ko, Y. (2021). Graph-based Fake News Detection using a Summarization Technique. Paper presented at the Proceedings of the 16th Conference of the European Chapter of the Association for Computational Linguistics: Main Volume.
    67. Kim, S., & Stoel, L. (2004). Apparel retailers: website quality dimensions and satisfaction. Journal of retailing and consumer services, 11(2), 109-117.
    68. Kiousis, S. (2006). Exploring the impact of modality on perceptions of credibility for online news stories. Journalism studies, 7(2), 348-359.
    69. Kolluri, N. L., & Murthy, D. (2021). CoVerifi: A COVID-19 news verification system. Online Social Networks and Media, 22, 100123.
    70. Lampos, V., Majumder, M. S., Yom-Tov, E., Edelstein, M., Moura, S., Hamada, Y., . . . Cox, I. J. (2021). Tracking COVID-19 using online search. NPJ digital medicine, 4(1), 1-11.
    71. Lazer, D., Baum, M., Grinberg, N., Friedland, L., Joseph, K., Hobbs, W., & Mattsson, C. (2017). Combating fake news: An agenda for research and action.
    72. Lazer, D. M., Baum, M. A., Benkler, Y., Berinsky, A. J., Greenhill, K. M., Menczer, F., . . . Rothschild, D. (2018). The science of fake news. Science, 359(6380), 1094-1096.
    73. Lee, H. K., Lee, J. S., & Keil, M. (2018). Using perspective-taking to de-escalate launch date commitment for products with known software defects. Journal of management information systems, 35(4), 1251-1276.
    74. Li, H., Daugherty, T., & Biocca, F. (2001). Characteristics of virtual experience in electronic commerce: A protocol analysis. Journal of interactive Marketing, 15(3), 13-30.
    75. Lloret, E., & Palomar, M. (2013). COMPENDIUM: a text summarisation tool for generating summaries of multiple purposes, domains, and genres. Natural Language Engineering, 19(2), 147-186.
    76. Longmire, N. H., & Harrison, D. A. (2018). Seeing their side versus feeling their pain: Differential consequences of perspective-taking and empathy at work. Journal of Applied Psychology, 103(8), 894.
    77. Lutzke, L., Drummond, C., Slovic, P., & Árvai, J. (2019). Priming critical thinking: Simple interventions limit the influence of fake news about climate change on Facebook. Global Environmental Change, 58, 101964.
    78. Lyons, B. A., Montgomery, J. M., Guess, A. M., Nyhan, B., & Reifler, J. (2021). Overconfidence in news judgments is associated with false news susceptibility. Proceedings of the National Academy of Sciences, 118(23).
    79. Müller, P., & Scherr, S. (2017). Reducing the bias: How perspective taking affects first-and third-person perceptions of media influence. Communication Research Reports, 34(2), 134-142.
    80. McGonagle, T. (2017). “Fake news” False fears or real concerns? Netherlands Quarterly of Human Rights, 35(4), 203-209.
    81. McGrew, S., Breakstone, J., Ortega, T., Smith, M., & Wineburg, S. (2018). Can students evaluate online sources? Learning from assessments of civic online reasoning. Theory & Research in Social Education, 46(2), 165-193.
    82. Mead, G. H., & Schubert, C. (1934). Mind, self and society (Vol. 111): University of Chicago press Chicago.
    83. 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.
    84. Meyer, P. (1988). Defining and measuring credibility of newspapers: Developing an index. Journalism quarterly, 65(3), 567-574.
    85. Mohr, P., Howells, K., Gerace, A., Day, A., & Wharton, M. (2007). The role of perspective taking in anger arousal. Personality and Individual Differences, 43(3), 507-517.
    86. Molina, M. D., Sundar, S. S., Le, T., & Lee, D. (2021). “Fake news” is not simply false information: A concept explication and taxonomy of online content. American behavioral scientist, 65(2), 180-212.
    87. Moore, D. A. (2005). Myopic biases in strategic social prediction: Why deadlines put everyone under more pressure than everyone else. Personality and social psychology bulletin, 31(5), 668-679.
    88. Mu, E., & Galletta, D. F. (2007). THE EFFECTS OF THE MEANINGFULNESS OF SALIENT BRAND AND PRODUCT-RELATED TEXT AND GRAPHCIS ON WEB SITE RECOGNITION. Journal of Electronic Commerce Research, 8(2).
    89. Ng, Y.-L., & Zhao, X. (2020). The human alarm system for sensational news, online news headlines, and associated generic digital footprints: A uses and gratifications approach. Communication Research, 47(2), 251-275.
    90. Nguyen, H., Santos, E., & Russell, J. (2011). Evaluation of the impact of user-cognitive styles on the assessment of text summarization. IEEE Transactions on Systems, Man, and Cybernetics-Part A: Systems and Humans, 41(6), 1038-1051.
    91. Noor, F. A. (2017). How “fake news” was a tool of nineteenth century colonialism and conquest. Media Asia, 44(2), 88-93.
    92. Parikh, S. B., Patil, V., & Atrey, P. K. (2019). On the origin, proliferation and tone of fake news. Paper presented at the 2019 IEEE Conference on Multimedia Information Processing and Retrieval (MIPR).
    93. Parker, S. K., & Axtell, C. M. (2001). Seeing another viewpoint: Antecedents and outcomes of employee perspective taking. Academy of Management Journal, 44(6), 1085-1100.
    94. Paschalides, D., Christodoulou, C., Andreou, R., Pallis, G., Dikaiakos, M. D., Kornilakis, A., & Markatos, E. (2019). Check-It: A plugin for detecting and reducing the spread of fake news and misinformation on the web. Paper presented at the 2019 IEEE/WIC/ACM International Conference on Web Intelligence (WI).
    95. 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), 1-12.
    96. Pennycook, G., & Rand, D. G. (2021). The psychology of fake news. Trends in cognitive sciences, 25(5), 388-402.
    97. Perloff, R. M. (1993). The dynamics of persuasion: Communication and attitudes in the 21st century: Routledge.
    98. Petinot, Y., McKeown, K., & Thadani, K. (2011). A hierarchical model of web summaries. Paper presented at the Proceedings of the 49th Annual Meeting of the Association for Computational Linguistics: Human Language Technologies.
    99. Pfeiffer, J., & Scholz, M. (2013). A low-effort recommendation system with high accuracy. Business & Information Systems Engineering, 5(6), 397-408.
    100. Rayner, K. (1978). Eye movements in reading and information processing. Psychological bulletin, 85(3), 618.
    101. Ren, Y., Kiesler, S., & Fussell, S. R. (2008). Multiple group coordination in complex and dynamic task environments: Interruptions, coping mechanisms, and technology recommendations. Journal of management information systems, 25(1), 105-130.
    102. Riedel, B., Augenstein, I., Spithourakis, G. P., & Riedel, S. (2017). A simple but tough-to-beat baseline for the Fake News Challenge stance detection task. arXiv preprint arXiv:1707.03264.
    103. Savage, S. J., & Waldman, D. M. (2008). Learning and fatigue during choice experiments: a comparison of online and mail survey modes. Journal of Applied Econometrics, 23(3), 351-371.
    104. Sessa, V. I. (1996). Using perspective taking to manage conflict and affect in teams. The Journal of applied behavioral science, 32(1), 101-115.
    105. Shariff, S. M., Zhang, X., & Sanderson, M. (2017). On the credibility perception of news on Twitter: Readers, topics and features. Computers in Human Behavior, 75, 785-796.
    106. Shu, K., Mahudeswaran, D., & Liu, H. (2019). FakeNewsTracker: a tool for fake news collection, detection, and visualization. Computational and Mathematical Organization Theory, 25(1), 60-71.
    107. Shu, K., Sliva, A., Wang, S., Tang, J., & Liu, H. (2017). Fake news detection on social media: A data mining perspective. ACM SIGKDD explorations newsletter, 19(1), 22-36.
    108. Singhal, S., Shah, R. R., Chakraborty, T., Kumaraguru, P., & Satoh, S. i. (2019). Spotfake: A multi-modal framework for fake news detection. Paper presented at the 2019 IEEE fifth international conference on multimedia big data (BigMM).
    109. Smith, A. (2010). The theory of moral sentiments: Penguin.
    110. Song, J. H., & Zinkhan, G. M. (2008). Determinants of perceived web site interactivity. Journal of marketing, 72(2), 99-113.
    111. Sousa, S., & Bates, N. (2021). Factors influencing content credibility in Facebook’s news feed. Human-Intelligent Systems Integration, 3(1), 69-78.
    112. Spencer, H. (1855). The principles of psychology. New York: D. Appleton & Company.
    113. Stefanone, M. A., Vollmer, M., & Covert, J. M. (2019). In news we trust? Examining credibility and sharing behaviors of fake news. Paper presented at the Proceedings of the 10th international conference on social media and society.
    114. Sundar, S. S. (2000). Multimedia effects on processing and perception of online news: A study of picture, audio, and video downloads. Journalism & Mass Communication Quarterly, 77(3), 480-499.
    115. Tandoc Jr, E. C., Lim, Z. W., & Ling, R. (2018). Defining “fake news” A typology of scholarly definitions. Digital journalism, 6(2), 137-153.
    116. Thon, F. M., & Jucks, R. (2017). Believing in expertise: How authors’ credentials and language use influence the credibility of online health information. Health communication, 32(7), 828-836.
    117. 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.
    118. Vescio, T. K., Sechrist, G. B., & Paolucci, M. P. (2003). Perspective taking and prejudice reduction: The mediational role of empathy arousal and situational attributions. European Journal of Social Psychology, 33(4), 455-472.
    119. Warren, I. D. (1969). The effect of credibility in sources of testimony on audience attitudes toward speaker and message.
    120. 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.
    121. 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.
    122. West, M. D. (1994). Validating a scale for the measurement of credibility: A covariance structure modeling approach. Journalism quarterly, 71(1), 159-168.
    123. Williams, H. M., Parker, S. K., & Turner, N. (2007). Perceived dissimilarity and perspective taking within work teams. Group & Organization Management, 32(5), 569-597.
    124. Yang, C. C., & Wang, F. L. (2008). Hierarchical summarization of large documents. Journal of the American Society for Information Science and Technology, 59(6), 887-902.
    125. Yu, C.-H., & Miller, R. C. (2012). Enhancing web page skimmability CHI`12 Extended Abstracts on Human Factors in Computing Systems (pp. 2655-2660).
    126. 林芃薇. (2015). 閱讀不同觀點文本對國小學生同理心與霸凌感受影響之實驗研究. (碩士), 國立臺灣師範大學, 台北市. Retrieved from https://hdl.handle.net/11296/377nk3
    127. 金樹人. (2010). 心理位移之結構特性及其辯證現象之分析：自我多重面向的敘寫與敘說. [Structure Characteristics of Psychological Displacement and Its Dialectical Phenomenon: Narratives of the Multidimensional Self]. 中華輔導與諮商學報(28), 187-229. doi: 10.7082/CJGC.201009.0187
    128. 黃宇弘. (2019). 大學生假新聞認知與教育看法研究.
    129. 蘇晉威. (2021). 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.
    Description: 碩士
    國立政治大學
    資訊管理學系
    109356035
    Source URI: http://thesis.lib.nccu.edu.tw/record/#G0109356035
    Data Type: thesis
    DOI: 10.6814/NCCU202201029
    Appears in Collections:[Department of MIS] Theses

    Files in This Item:

    File Description SizeFormat
    603501.pdf2095KbAdobe PDF20View/Open


    All items in 政大典藏 are protected by copyright, with all rights reserved.


    社群 sharing

    著作權政策宣告 Copyright Announcement
    1.本網站之數位內容為國立政治大學所收錄之機構典藏，無償提供學術研究與公眾教育等公益性使用，惟仍請適度，合理使用本網站之內容，以尊重著作權人之權益。商業上之利用，則請先取得著作權人之授權。
    The digital content of this website is part of National Chengchi University Institutional Repository. It provides free access to academic research and public education for non-commercial use. Please utilize it in a proper and reasonable manner and respect the rights of copyright owners. For commercial use, please obtain authorization from the copyright owner in advance.

    2.本網站之製作，已盡力防止侵害著作權人之權益，如仍發現本網站之數位內容有侵害著作權人權益情事者，請權利人通知本網站維護人員(nccur@nccu.edu.tw)，維護人員將立即採取移除該數位著作等補救措施。
    NCCU Institutional Repository is made to protect the interests of copyright owners. If you believe that any material on the website infringes copyright, please contact our staff(nccur@nccu.edu.tw). We will remove the work from the repository and investigate your claim.
    DSpace Software Copyright © 2002-2004  MIT &  Hewlett-Packard  /   Enhanced by   NTU Library IR team Copyright ©   - Feedback