Earticle

초록

영어

Social media is increasingly being used as a source of information during crises, such as natural disasters and civil unrests. However, the quality and truthfulness of user-generated information on social media have been a cause of concern. Many users find distinguishing between true and false information on social media difficult. Basing on the elaboration likelihood model and the motivation, opportunity, and ability framework, this study proposes and empirically tests a model that identifies the information processing routes through which users develop trust, as well as the factors that influence the use of these routes. The findings from a survey of Twitter users seeking information about the Fukushima Daiichi nuclear crisis indicate that individuals evaluate information quality more when the crisis information has strong personal relevance or when individuals have low anxiety about the crisis. By contrast, they rely on majority influence more when the crisis information has less personal relevance or when these individuals have high anxiety about the crisis. Prior knowledge does not have significant moderating effects on the use of information quality and majority influence in forming trust. This study extends the theorization of trust in user-generated information by focusing on the process through which users form trust. The findings also highlight the need to alleviate anxiety and manage non-victims in controlling the spread of false information on social media during crises.

목차

ABSTRACT
 Ⅰ. Introduction
 Ⅱ. Conceptual Background
  2.1. Trust in User-Generated Information on the Internet
  2.2. Elaboration Likelihood Model (ELM)
  2.3. Motivation, Opportunity and Ability (MOA) Framework
 Ⅲ. Research Model and Hypotheses
  3.1. Moderating Effects of Personal Relevance
  3.2. Moderating Effects of Anxiety
  3.3. Moderating Effects of Prior Knowledge
 Ⅳ. Research Method
  4.1. Development of Survey Instrument
  4.2. Data Collection and Sample Demographics
 Ⅴ. Data Analysis and Results
  5.1. Tests of Measurement Model
  5.2. Tests of Structural Model
 Ⅵ. Discussion
  6.1. Implications for Research
  6.2. Implications for Practice
  6.3. Conclusion
 

저자

• L. G. Pee [ Assistant Professor, Wee Kim Wee School of Communication, and Information, Nanyang Technological University (NTU), Singapore ]
• Jung Lee [ Associate Professor, College of Economics and Business, Hankuk University of Foreign Studies, Korea ] Corresponding Author

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