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Rumor and Truth Spreading Patterns on Social Network Sites During Social Crisis: Big Data Analytics Approach

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E-Life: Web-Enabled Convergence of Commerce, Work, and Social Life (WEB 2015)

Part of the book series: Lecture Notes in Business Information Processing ((LNBIP,volume 258))

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Abstract

Social network sites give their users the ability to create contents and share it with others. During social crisis, the spread of false and true information could have profound impacts on users. Lack of prior studies to compare differences between diffusion patterns of rumors and truths during social crisis is the motivation of this study. In this study, we examine the role of information credibility, anxiety, personal involvement, and social ties on rumor and truth spread during social crisis. Building on the rumor theory, we propose a research model to examine differences between spread of rumors and truths. Using the Tweeter data collected during the Baltimore riots in 2015, we test the research model. Theoretical contributions and practical implications will be outlined based on the findings of the study. We anticipate findings will provide new avenues of research by determining characteristics of truths and rumors in online contexts.

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Author information

Authors and Affiliations

  1. School of Business, University of Redlands, Redlands, CA, USA

    Mehrdad Koohikamali

  2. ITDS Department, College of Business, University of North Texas, Denton, TX, USA

    Mehrdad Koohikamali & Dan J. Kim

Authors
  1. Mehrdad Koohikamali
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  2. Dan J. Kim
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Corresponding author

Correspondence to Mehrdad Koohikamali .

Editor information

Editors and Affiliations

  1. Department of Decision and Information Sciences, Oakland University, Rochester, Michigan, USA

    Vijayan Sugumaran

  2. Virginia Commonwealth University, Richmond, Virginia, USA

    Victoria Yoon

  3. Beckman Institute for Advanced Science and Technology, University of Illinois at Urbana–Champaign, Urbana, Illinois, USA

    Michael J. Shaw

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© 2016 Springer International Publishing Switzerland

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Koohikamali, M., Kim, D.J. (2016). Rumor and Truth Spreading Patterns on Social Network Sites During Social Crisis: Big Data Analytics Approach. In: Sugumaran, V., Yoon, V., Shaw, M. (eds) E-Life: Web-Enabled Convergence of Commerce, Work, and Social Life. WEB 2015. Lecture Notes in Business Information Processing, vol 258. Springer, Cham. https://doi.org/10.1007/978-3-319-45408-5_15

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