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| DC 欄位 | 值 | 語言 |
|---|---|---|
| dc.contributor.advisor | 唐牧群(Muh-Chyun Tang) | |
| dc.contributor.author | I-Hsiang Chia | en |
| dc.contributor.author | 賈逸翔 | zh_TW |
| dc.date.accessioned | 2021-06-16T09:21:43Z | - |
| dc.date.available | 2018-07-12 | |
| dc.date.copyright | 2017-07-12 | |
| dc.date.issued | 2017 | |
| dc.date.submitted | 2017-06-28 | |
| dc.identifier.citation | Albarracín, D. (2002). Cognition in persuasion: An analysis of information processing in response to persuasive communications. In M. P. Zanna (Ed.), Advances in Experimental Social Psychology (pp. 61-130). San Diego, California, CA: Academic Press., 61–130.
Arora, N. K., Hesse, B. W., Rimer, B. K., Viswanath, K., Clayman, M. L., & Croyle, R. T. (2008). Frustrated and Confused: The American Public Rates its Cancer-Related Information-Seeking Experiences. Journal of General Internal Medicine, 23(3), 223–228. https://doi.org/10.1007/s11606-007-0406-y Bientzle, M., Cress, U., & Kimmerle, J. (2013). How students deal with inconsistencies in health knowledge. Medical Education, 47(7), 683–690. https://doi.org/10.1111/medu.12198 Brannon, L. A., Tagler, M. J., & Eagly, A. H. (2007). The moderating role of attitude strength in selective exposure to information. Journal of Experimental Social Psychology, 43(4), 611–617. https://doi.org/10.1016/j.jesp.2006.05.001 Brehm, J. W., & Cohen, A. R. (1962). Explorations in cognitive dissonance. Hoboken, NJ, US: John Wiley & Sons Inc Explorations in cognitive dissonance. xiv 334 pp. Briggs, P., Burford, B., De Angeli, A., & Lynch, P. (2002). Trust in Online Advice. Social Science Computer Review, 20(3), 321–332. Briggs, P., Simpson, B., & Angeli, A. D. (2004). Personalisation and Trust: A Reciprocal Relationship? In C.-M. Karat, J. O. Blom, & J. Karat (Eds.), Designing Personalized User Experiences in eCommerce (pp. 39–55). Springer Netherlands. https://doi.org/10.1007/1-4020-2148-8_4 Buder, J., & Schwind, C. (2012). Learning with personalized recommender systems: A psychological view. Computers in Human Behavior, 28(1), 207–216. https://doi.org/10.1016/j.chb.2011.09.002 Buder, J., Schwind, C., Rudat, A., & Bodemer, D. (2015). Selective reading of large online forum discussions: The impact of rating visualizations on navigation and learning. Computers in Human Behavior, 44, 191–201. Chaiken, S. (1980). Heuristic versus systematic information processing and the use of source versus message cues in persuasion. Journal of Personality, 39(5), 752–766. Chaiken, S., Wood, W., & Eagly, A. H. (1996). Principles of persuasion. In E. T. Higgins & A. W. Kruglanski (Eds.), Social psychology: Handbook of basic principles (pp. 702–742). New York, NY, US: Guilford Press. Chitika, I. (2013). The value of Google result positioning. Online Advertising Network. Retrieved from https://justmythinking.com/wp-content/uploads/2015/07/ChitikaInsights-ValueofGoogleResultsPositioning.pdf De Mello, G. E. (2004). In need of a favorable conclusion: The role of goal-motivated reasoning in consumer judgments and evaluations. Summarised Version of Dissertation: University of Southern California. Retrieved from http://elibrary.ru/item.asp?id=9347046 DiFonzo, N., Robinson, N. M., Suls, J. M., & Rini, C. (2012). Rumors About Cancer: Content, Sources, Coping, Transmission, and Belief. Journal of Health Communication, 17(9), 1099–1115. https://doi.org/10.1080/10810730.2012.665417 Doise, W., & Mugny, G. (1984). The social development of the intellect (Vol. 10). Oxford, UK: Pergamon Press. Dutta-Bergman, M. J. (2004). The impact of completeness and web use motivation on the credibility of e-health information. Journal of Communication, 54(2), 253–269. https://doi.org/10.1093/joc/54.2.253 Eagly, A. H. (1978). Sex differences in influenceability. Psychological Bulletin, 85(1), 86–116. Eysenbach, G., & Jadad, A. R. (2001). Evidence-based Patient Choice and Consumer health informatics in the Internet age. Journal of Medical Internet Research, 3(2), e19. https://doi.org/10.2196/jmir.3.2.e19 Eysenbach, G., & Köhler, C. (2002). How do consumers search for and appraise health information on the world wide web? Qualitative study using focus groups, usability tests, and in-depth interviews. BMJ, 324(7337), 573–577. https://doi.org/10.1136/bmj.324.7337.573 Festinger, L. (1957). A theory of cognitive dissonance (Vol. 2). Redwood City, California, CA: Stanford university press. Festinger, L. (1964). Conflict, decision, and dissonance (Vol. 3). Redwood City, California, CA: Stanford university press. Fischer, P., Jonas, E., Frey, D., & Kastenmüller, A. (2008). Selective exposure and decision framing: The impact of gain and loss framing on confirmatory information search after decisions. Journal of Experimental Social Psychology, 44(2), 312–320. https://doi.org/10.1016/j.jesp.2007.06.001 Fox, S., & Duggan, M. (2013). Health online 2013. Washington, DC: Pew Internet & American Life Project. Retrieved from http://bibliobase.sermais.pt:8008/BiblioNET/Upload/PDF5/003820.pdf Fox, S., & Rainie, L. (2002a). Vital decisions: how Internet users decide what information to trust when they or their loved ones are sick. ResearchGate. Fox, S., & Rainie, L. (2002b). Vital Decisions: How Internet Users Decide what Information to Trust when They or Their Loved Ones are Sick: Plus a Guide from the Medical Library Association about Smart Health-search Strategies and Good Web Sites (Page 32). Pew Internet & American Life Project. Frey, D. (1981). Postdecisional preference for decision-relevant information as a function of the competence of its source and the degree of familiarity with this information. Journal of Experimental Social Psychology, 17(1), 51–67. https://doi.org/10.1016/0022-1031(81)90006-8 Frey, D. (1982). Different levels of cognitive dissonance, information seeking, and information avoidance. Journal of Personality, 43(6), 1175–1183. Frey, D. (1985). Amount of available information and selective exposure. Unpublished Manuscript, Christian-Albrechts-University, Kiel. Frey, D. (1986). Recent Research on Selective Exposure to Information. In L. Berkowitz (Ed.), Advances in Experimental Social Psychology (Vol. 19, pp. 41–80). Academic Press. Hack, T. F., Degner, L. F., & Dyck, D. G. (1994). Relationship between preferences for decisional control and illness information among women with breast cancer: A quantitative and qualitative analysis. Social Science & Medicine, 39(2), 279–289. https://doi.org/10.1016/0277-9536(94)90336-0 Hart, W., Albarracín, D., Eagly, A. H., Brechan, I., Lindberg, M. J., & Merrill, L. (2009). Feeling Validated Versus Being Correct:A Meta-Analysis of Selective Exposure to Information. Psychological Bulletin, 135(4), 555–588. https://doi.org/10.1037/a0015701 Hienerth, C., & Riar, F. (2013). The wisdom of the crowd vs. expert evaluation: A conceptualization of evaluation validity. In 35th DRUID Celebration Conference, Barcelona, Spain, June (pp. 17–19). Horne, D. C. (1999). A Medical Library for the Public: Starting and Running A Consumer Healthy Library. North Carolina Libraries, 57(3). https://doi.org/10.3776/ncl.v57i3.3051 Jans, L. C., & Kranzbühler, A. M. (2015). The influence of rating volume in the effects of expert versus patient online ratings. Acta orthopaedica Belgica, 81(4), 662-667. Johnson, B. T. (1994). Effects of Outcome-Relevant Involvement and Prior Information on Persuasion. Journal of Experimental Social Psychology, 30(6), 556–579. https://doi.org/10.1006/jesp.1994.1026 Johnson, B. T., & Eagly, A. H. (1989). Effects of Involvement on Persuasion: A Meta-Analysis. [Review]. Psychological Bulletin, 106(2), 290–314. Johnson, D. W., Johnson, R. T., & Smith, K. A. (2000). Constructive Controversy. Change, 32(1), 28. Jonas, E., Schulz-Hardt, S., Frey, D., & Thelen, N. (2001). Confirmation bias in sequential information search after preliminary decisions: An expansion of dissonance theoretical research on selective exposure to information. Journal of Personality and Social Psychology, 80(4), 557–571. https://doi.org/10.1037//0022-3514.80.4.557 Kaba, R., & Sooriakumaran, P. (2007). The evolution of the doctor-patient relationship. International Journal of Surgery, 5(1), 57–65. https://doi.org/10.1016/j.ijsu.2006.01.005 Kalbach, J. (2004). Feeling Lucky?: Emotions and Information Seeking. Interactions, 11(5), 66–67. https://doi.org/10.1145/1015530.1015563 Kruglanski, A. W. (1989). Lay epistemics and human knowledge. New York, NY: Plenum Press. Kruglanski, A. W., & Ajzen, I. (1983). Bias and error in human judgment. European Journal of Social Psychology, 13(1), 1–44. https://doi.org/10.1002/ejsp.2420130102 Kuhlthau, C. C. (1993). Seeking Meaning: A Process Approach to Library and Information Services. Ablex Publishing Corporation. Kuhlthau, C. C. (2005). Towards collaboration between information seeking and information retrieval. Information Research: An International Electronic Journal, 10(2), n2. Lagan, B. M., Sinclair, M., & George Kernohan, W. (2010). Internet Use in Pregnancy Informs Women’s Decision Making: A Web-Based Survey. Birth, 37(2), 106–115. https://doi.org/10.1111/j.1523-536X.2010.00390.x Lau, A. Y. S., & Coiera, E. W. (2006). A Bayesian model that predicts the impact of Web searching on decision making. Journal of the American Society for Information Science and Technology, 57(7), 873–880. https://doi.org/10.1002/asi.20377 Lau, A. Y. S., & Coiera, E. W. (2007). Do People Experience Cognitive Biases while Searching for Information? Journal of the American Medical Informatics Association : JAMIA, 14(5), 599–608. https://doi.org/10.1197/jamia.M2411 Liao, Q. V., Fu, W.-T., & Mamidi, S. S. (2015). It Is All About Perspective: An Exploration of Mitigating Selective Exposure with Aspect Indicators. In Proceedings of the 33rd Annual ACM Conference on Human Factors in Computing Systems (pp. 1439–1448). New York, NY, USA: ACM. https://doi.org/10.1145/2702123.2702570 Longo, D. R. (2005). Understanding health information, communication, and information seeking of patients and consumers: a comprehensive and integrated model. Health Expectations, 8(3), 189–194. https://doi.org/10.1111/j.1369-7625.2005.00339.x Mead, N., Varnam, R., Rogers, A., & Roland, M. (2003). What Predicts Patients’ Interest in the Internet as a Health Resource in Primary Care in England? Journal of Health Services Research & Policy, 8(1), 33–39. https://doi.org/10.1177/135581960300800108 Mishra, J., Allen, D., & Pearman, A. (2015). Information seeking, use, and decision making. Journal of the Association for Information Science and Technology, 66(4), 662–673. https://doi.org/10.1002/asi.23204 Muller, C. (1990). Health care and gender. Russell sage foundation. Nemeth, C., & Rogers, J. (1996). Dissent and the search for information. British Journal of Social Psychology, 35(1), 67–76. https://doi.org/10.1111/j.2044-8309.1996.tb01083.x Oh, S. (2012). The characteristics and motivations of health answerers for sharing information, knowledge, and experiences in online environments. Journal of the American Society for Information Science and Technology, 63(3), 543–557. https://doi.org/10.1002/asi.21676 Park, D. H., Lee, J., & Han, I. (2007). The Effect of On-Line Consumer Reviews on Consumer Purchasing Intention: The Moderating Role of Involvement. International Journal of Electronic Commerce, 11(4), 125–148. https://doi.org/10.2753/JEC1086-4415110405 Petty, R., & Cacioppo, J. T. (1986). Communication and persuasion: Central and peripheral routes to attitude change. New York: Springer-Verlag. Petty, R. E., & Cacioppo, J. T. (1980). Sex Differences in Influenceability Toward Specifying the Underlying Processes. Personality and Social Psychology Bulletin, 6(4), 651–656. https://doi.org/10.1177/014616728064016 Petty, R. E., & Cacioppo, J. T. (1986). The Elaboration Likelihood Model of Persuasion. Advances in Experimental Social Psychology, 19(C), 123–205. https://doi.org/10.1016/S0065-2601(08)60214-2 Petty, R. E., Cacioppo, J. T., & Goldman, R. (1981). Personal involvement as a determinant of argument-based persuasion. Journal of Personality, 41(5), 847–855. Potts, H. W. W., & Wyatt, J. C. (2002). Survey of Doctors’ Experience of Patients Using the Internet. Journal of Medical Internet Research, 4(1), e5. https://doi.org/10.2196/jmir.4.1.e5 Preece, J. (1998). Empathic Communities: Reaching out Across the Web. Interactions, 5(2), 32–43. https://doi.org/10.1145/274430.274435 Raju, S., Unnava, H. R., & Montgomery, N. V. (2009). The Effect of Brand Commitment on the Evaluation of Nonpreferred Brands: A Disconfirmation Process. Journal of Consumer Research, 35(5), 851–863. Rutten, L. J. F., Arora, N. K., Bakos, A. D., Aziz, N., & Rowland, J. (2005). Information needs and sources of information among cancer patients: a systematic review of research (1980–2003). Patient Education and Counseling, 57(3), 250–261. https://doi.org/10.1016/j.pec.2004.06.006 Schweiger, S., Oeberst, A., & Cress, U. (2014). Confirmation Bias in Web-Based Search: A Randomized Online Study on the Effects of Expert Information and Social Tags on Information Search and Evaluation. Journal of Medical Internet Research, 16(3). https://doi.org/10.2196/jmir.3044 Schwind, C., & Buder, J. (2012). Reducing confirmation bias and evaluation bias: When are preference-inconsistent recommendations effective – and when not? Computers in Human Behavior, 28(6), 2280–2290. https://doi.org/10.1016/j.chb.2012.06.035 Schwind, C., Buder, J., Cress, U., & Hesse, F. W. (2012). Preference-inconsistent recommendations: An effective approach for reducing confirmation bias and stimulating divergent thinking? Computers & Education, 58(2), 787–796. https://doi.org/10.1016/j.compedu.2011.10.003 Senecal, S., & Nantel, J. (2004). The influence of online product recommendations on consumers’ online choices. Journal of Retailing, 80(2), 159–169. https://doi.org/10.1016/j.jretai.2004.04.001 Sillence, E., Briggs, P., Harris, P. R., & Fishwick, L. (2007). How do patients evaluate and make use of online health information? Social Science & Medicine, 64(9), 1853–1862. https://doi.org/10.1016/j.socscimed.2007.01.012 Surowiecki, J. (2005). The wisdom of crowds. Anchor books. Tesser, A., Martin, L., & Mendolia, M. (1995). The impact of thought on attitude extremity and attitude-behavior consistency. In R. E. Petty & J.A. Krosnick (Eds.), Attitude strength: Antecedents and consequences (pp. 73-92). Mahwah, NJ: Erlbaum. Toms, E. G., Freund, L., Kopak, R., & Bartlett, J. C. (2003). The Effect of Task Domain on Search. In Proceedings of the 2003 Conference of the Centre for Advanced Studies on Collaborative Research (pp. 303–312). Toronto, Ontario, Canada: IBM Press. Van Knippenberg, D., De Dreu, C. K., & Homan, A. C. (2004). Work group diversity and group performance: an integrative model and research agenda. Journal of Applied Psychology, 89(6), 1008. Vydiswaran, V. G. V., Zhai, C., Roth, D., & Pirolli, P. (2015). Overcoming bias to learn about controversial topics. Journal of the Association for Information Science and Technology, 66(8), 1655–1672. https://doi.org/10.1002/asi.23274 Wang, L., Wang, J., Wang, M., Li, Y., Liang, Y., & Xu, D. (2012). Using Internet Search Engines to Obtain Medical Information: A Comparative Study. Journal of Medical Internet Research, 14(3). https://doi.org/10.2196/jmir.1943 Wilson, T. (1999). Exploring models of information behaviour: the ‘uncertainty’ project. Information Processing & Management, 35(6), 839–849. https://doi.org/10.1016/S0306-4573(99)00029-1 Xiao, B., & Benbasat, I. (2007). E-Commerce Product Recommendation Agents: Use, Characteristics, and Impact. MIS Quarterly, 31(1), 137–209. Zhang, Y. (2013). Toward a layered model of context for health information searching: An analysis of consumer-generated questions. Journal of the American Society for Information Science and Technology, 64(6), 1158–1172. https://doi.org/10.1002/asi.22821 張育真(2013)。大專院校學生網路消費者健康資訊尋求歷程研究(碩士論文)。國立台灣大學，台北市。 羅文伶、邱銘心(2015)。網路健康謠言內容分析研究。教育資料與圖書館學，52(1)， 3–31。 邱銘心、張家翎(2015)。網路醫師評價之結構與內容特徵分析研究。教育資料與圖書館學，52(2)，157–190。 邱銘心、范卉妤、陳德雯(2014)。探討網路醫療諮詢之角色: 從台灣 e 院的醫師回答談起。醫療資訊雜誌，23(4)，21–35。 鄭惟中、邱銘心(2015)。我國政府衛生福利機關 (構) 網站提供消費者健康資訊服務之初探。大學圖書館，19(2)，69–107。 | |
| dc.identifier.uri | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/59369 | - |
| dc.description.abstract | 確認偏誤是一種資訊尋求者在找資訊時傾向找尋符合自己原先立場資訊之行為，它可能會阻礙消費者健康資訊尋求行為並導致錯誤的決策。前人研究顯示，透過系統推薦對立立場的資訊給使用者，可以降低他們的確認偏誤。本實驗探討專家推薦系統與大眾推薦系統降低確認偏誤的效果，並在選擇階段、評估階段和最終決策階段分別測量確認偏誤的大小。本實驗招募了 78 位 40 到 70 歲的受測者。受測者只被告知他們參加的是針對兩個癌症篩檢議題的健康資訊實驗。實驗設計讓受測者在兩個不同篩檢議題下會使用到兩個不同的推薦系統。實驗結果發現和選擇偏誤相比，評估偏誤和最終決策偏誤較難被抵銷。在降低選擇偏誤上，專家推薦系統比大眾推薦系統效果更好。此外，專家推薦系統對高涉入感的議題影響力也較佳。本實驗亦發現面對健康資訊議題，樣本存在性別差異。未來研究降低確認偏誤的研究者應視性別為一項干擾變項並選擇大眾認知程度相近的健康議題作為實驗材料，方能達到更準確的研究成果。 | zh_TW |
| dc.description.abstract | Confirmation bias, the preferential seeking of confirmatory information, can become an obstacle for the disseminate of valid health information online and lead to biased decision. Following previous findings, preference-inconsistent recommendation can be used to overcome this bias. We conducted an experiment to study the impact of expert system and popularity system on mitigating confirmation bias, the confirmation bias was measured in the selection phase, the evaluation phase and the final decision phases. 78 participants aged 40-70 were recruited. Participants were informed that they would participate in a health information experiment involving two cancer screening debates. Participants were assigned in such a way that each participant would see two fairly different interfaces for the two tasks. We found that the evaluation bias and the final decision were more persistent than the selection bias. The comparison between the two systems revealed that expert system has a better mitigation effect than the popularity system in the selection bias. Furthermore, it was observed that expert system would have better mitigation effect on high-involvement issue. We also found strong gender difference in our experiment. Future study which aims to investigate the mitigation effect of different techniques should take gender as a confounding variable and choose health issues which are more comparable. | en |
| dc.description.provenance | Made available in DSpace on 2021-06-16T09:21:43Z (GMT). No. of bitstreams: 1 ntu-106-R03126001-1.pdf: 5955567 bytes, checksum: a3820f4b621337640d7852141d246c25 (MD5) Previous issue date: 2017 | en |
| dc.description.tableofcontents | 1 Introduction 1
1.1 Problem statement 1 1.1.1 Introductory paragraph 1 1.1.2 Background of the problem 4 1.1.3 Statement of the problem 7 1.2 Purpose of the study 8 1.2.1 Primary research questions and hypothesis 10 1.2.2 Significance of the study 12 1.2.3 Research contribution 14 1.3 Assumptions, scope and limitations 14 1.4 Definition of terms 17 1.4.1 Confirmation bias 17 1.4.2 De-biasing techniques 18 1.4.3 Elaboration likelihood model (ELM) 19 1.4.4 Involvement 19 2 Literature review 21 2.1 Health information seeking and decision making 21 2.2 Confirmation bias 26 2.2.1 Introduction 26 2.2.2 Polarization 29 2.2.3 De-biasing techniques 33 2.3 Elaboration likelihood model 37 2.3.1 Routes 37 2.3.2 Ability 38 2.3.3 Motivation (Involvement) 39 2.3.4 Variables 42 3 Method 43 3.1 Participants 43 3.2 Design 45 3.3 Procedure 46 3.4 Instrument material 55 3.4.1 Issue 55 3.4.2 Background statement, background knowledge questions and involvement questions 56 3.4.3 Experiment interface 59 3.4.4 System 59 3.5 Data analysis 63 3.5.1 Independent and control variables 64 3.5.2 Dependent variables 65 3.5.3 Manipulation check 67 3.5.4 Reliability and validity 67 3.5.5 Material persuasiveness pretest 68 3.5.6 Procedure pretest 79 4 Results 80 4.1 Demographics 80 4.2 Reliability 82 4.3 Manipulation check 83 4.4 Selection bias 90 4.4.1 The selection bias for individual search results 90 4.4.2 Participants’ selection bias 93 4.5 Evaluation bias 100 4.6 Final decision bias 115 5 Discussion and conclusion 123 5.1 Discussion 123 5.1.1 Confirmation bias in information processing 123 5.1.2 The effects of different de-bias techniques and the role of involvement 124 5.1.3 the selection bias 128 5.1.4 the relation between selection bias and evaluation bias 128 5.1.5 the final decision bias 130 5.1.6 Expert system effect 133 5.1.7 Gender difference 134 5.1.8 Limitations 134 5.2 Conclusion 137 5.3 Future application 137 Reference……………………………………………………………………………142 Appendix……………………………………………………………………………154 | |
| dc.language.iso | en | |
| dc.subject | 確認偏誤 | zh_TW |
| dc.subject | 涉入感 | zh_TW |
| dc.subject | 評估偏誤 | zh_TW |
| dc.subject | 選擇性接收 | zh_TW |
| dc.subject | 健康資訊處理 | zh_TW |
| dc.subject | selective exposure | en |
| dc.subject | involvement | en |
| dc.subject | evaluation bias | en |
| dc.subject | health information processing | en |
| dc.subject | confirmation bias | en |
| dc.title | 比較大眾意見與專家意見對於降低健康資訊之確認偏誤的效果 | zh_TW |
| dc.title | The Mitigation of Confirmation Bias in Health Information processing: a Comparison between Popular and Expert Opinions | en |
| dc.type | Thesis | |
| dc.date.schoolyear | 105-2 | |
| dc.description.degree | 碩士 | |
| dc.contributor.oralexamcommittee | 蔡天怡(Tien-I Tsai),邱銘心(Ming-Hsin Chiu) | |
| dc.subject.keyword | 健康資訊處理,確認偏誤,選擇性接收,評估偏誤,涉入感, | zh_TW |
| dc.subject.keyword | health information processing,confirmation bias,selective exposure,evaluation bias,involvement, | en |
| dc.relation.page | 216 | |
| dc.identifier.doi | 10.6342/NTU201701167 | |
| dc.rights.note | 有償授權 | |
| dc.date.accepted | 2017-06-28 | |
| dc.contributor.author-college | 文學院 | zh_TW |
| dc.contributor.author-dept | 圖書資訊學研究所 | zh_TW |
| 顯示於系所單位： | 圖書資訊學系 | |
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