Trust of Information on Social Media: An Elaboration Likelihood Model

Social media such as Twitter and Facebook are increasingly being used as a source of information in critical situations such as natural disasters and civil unrests. However, false information exists on social media and trusting false information not only leads users to make wrong decisions but can also have dire impact on the society. This research-in-progress examines how individuals process information on social media to determine whether or not to trust the information. Based on the elaboration likelihood model, a research model elucidating the effects of information quality, source credibility, and majority influence on users’ trust of information on social media is proposed. Further, the moderating effects of personal involvement and users’ prior knowledge are investigated. Results from a pilot survey indicate that majority influence has a stronger effect on trust than source credibility for social media users and they are likely to rely on information quality as well as source credibility and majority influence when their personal involvement is high.

[1]  Franziska Marquart,et al.  Communication and persuasion : central and peripheral routes to attitude change , 1988 .

[2]  Jaap J. Dijkstra,et al.  User agreement with incorrect expert system advice , 1999, Behav. Inf. Technol..

[3]  Hee-Woong Kim,et al.  A balanced thinking-feelings model of information systems continuance , 2007, Int. J. Hum. Comput. Stud..

[4]  Diane M. Strong,et al.  AIMQ: a methodology for information quality assessment , 2002, Inf. Manag..

[5]  D. Kerstetter,et al.  Prior knowledge, credibility and information search , 2004 .

[6]  A. Bandura.  Health Promotion by Social Cognitive Means , 2004, Health education & behavior : the official publication of the Society for Public Health Education.

[7]  Adam Acar,et al.  Twitter for crisis communication: lessons learned from Japan's tsunami disaster , 2011, Int. J. Web Based Communities.

[8]  R. Apsler,et al.  Warning, personal involvement, and attitude change. , 1968, Journal of personality and social psychology.

[9]  C. Nemeth.  Differential contributions of majority and minority influence , 1986 .

[10]  R. Cialdini.  Influence: Science and Practice , 1984 .

[11]  Mary Beth Rosson,et al.  How and why people Twitter: the role that micro-blogging plays in informal communication at work , 2009, GROUP.

[12]  TamKar Yan,et al.  Web Personalization as a Persuasion Strategy , 2005 .

[13]  Hosung Park,et al.  What is Twitter, a social network or a news media? , 2010, WWW '10.

[14]  Stephanie Watts,et al.  Informational Influence in Organizations: An Integrated Approach to Knowledge Adoption , 2003, Inf. Syst. Res..

[15]  SussmanStephanie Watts,et al.  Informational Influence in Organizations , 2003 .

[16]  S. Chaiken,et al.  Heuristic processing can bias systematic processing: effects of source credibility, argument ambiguity, and task importance on attitude judgment. , 1994, Journal of personality and social psychology.

[17]  Gerd Bohner,et al.  Beyond Conflict and Discrepancy: Cognitive Bias in Minority and Majority Influence , 1998 .

[18]  Diane M. Mackie,et al.  Systematic and nonsystematic processing of majority and minority persuasive communications. , 1987 .

[19]  Barbara Poblete,et al.  Twitter under crisis: can we trust what we RT? , 2010, SOMA '10.

[20]  Izak Benbasat,et al.  The Effects of Personalizaion and Familiarity on Trust and Adoption of Recommendation Agents , 2006, MIS Q..

[21]  Ritu Agarwal,et al.  Adoption of Electronic Health Records in the Presence of Privacy Concerns: The Elaboration Likelihood Model and Individual Persuasion , 2009, MIS Q..

[22]  Chanthika Pornpitakpan.  The Persuasiveness of Source Credibility: A Critical Review of Five Decades' Evidence , 2004 .

[23]  S. Shyam Sundar,et al.  Effects of Online Health Sources on Credibility and Behavioral Intentions , 2010, Commun. Res..

[24]  Soo Young Rieh.  Judgment of information quality and cognitive authority in the Web , 2002, J. Assoc. Inf. Sci. Technol..

[25]  G. Eysenbach.  Medicine 2.0: Social Networking, Collaboration, Participation, Apomediation, and Openness , 2008, Journal of medical Internet research.

[26]  Shuk Ying Ho,et al.  Web Personalization as a Persuasion Strategy: An Elaboration Likelihood Model Perspective , 2005, Inf. Syst. Res..

[27]  Michael J. Muller,et al.  Motivations for social networking at work , 2008, CSCW.

[28]  J. Golbeck,et al.  FilmTrust: movie recommendations using trust in web-based social networks , 2006, CCNC 2006. 2006 3rd IEEE Consumer Communications and Networking Conference, 2006..

[29]  C. Farn,et al.  Investigating Initial Trust Toward E-tailers from the Elaboration Likelihood Model Perspective , 2006 .

[30]  Soo Young Rieh.  Judgement of information quality and cognitive authority in the Web , 2002 .

[31]  Anol Bhattacherjee,et al.  Influence Processes for Information Technology Acceptance: An Elaboration Likelihood Model , 2006, MIS Q..

[32]  Kalle Lyytinen,et al.  User participation in knowledge update of expert systems , 1997, Inf. Manag..

[33]  Wenhong Luo,et al.  Trust-building measures: a review of consumer health portals , 2004, CACM.

[34]  Shu-Chuan Chu,et al.  The Effect of Perceived Blogger Credibility and Argument Quality on Message Elaboration and Brand Attitudes , 2008 .

[35]  Charles A. O'Reilly,et al.  Variations in Decision Makers' Use of Information Sources: The Impact of Quality and Accessibility of Information , 1982 .

[36]  Li Yang,et al.  Who will you ask? An empirical study of interpersonal task information seeking , 2006, J. Assoc. Inf. Sci. Technol..