Social Big Data Analysis of Information Spread and Perceived Infection Risk during the 2015 Middle East Respiratory Syndrome Outbreak in South Korea

Juyoung Song, Tae Min Song, Dong Chul Seo, Dal Lae Jin, Jung Sun Kim

Research output: Contribution to journalArticlepeer-review

42 Scopus citations

Abstract

We investigated online diffusion of information, spread of fear, and perceived risk of infection to Middle East Respiratory Syndrome (MERS) as cases of MERS spread rapidly and dozens of fatalities occurred in South Korea in May-June of 2015. This study retrieved 8,671,695 MERS-related online documents from May 20 to June 18, 2015, from 171 Korean online channels and analyzed such documents by using multilevel models and data mining with Apriori algorithm association analysis. We used R software (version 3.2.1) for the association analysis data mining and visualization. Buzz with negative emotions (i.e., anxiety or fear) was more prevalent in online discussion boards, Twitter, and online cafes than news sites and blogs. News buzz (b = 0.21, p < 0.001), but not rumor buzz (b = 0.06, p = 0.308), was associated with positive MERS emotions (i.e., being calm or composed). The mention of eating immunity-boosting food in the news led to a 94 percent chance of a positive MERS emotion and that such a chance of showing a positive emotion was 4.75 times higher than that without such a mention (support of 0.001, confidence of 0.94, and lift of 4.75). Even with the same precautionary messages that were disseminated, they yielded the opposite emotional reactions to people depending on the channel through which the messages were communicated. In the face of a novel and highly contagious disease such as MERS, the government must deploy a response system that includes provision and dissemination of reliable information and inhibits online diffusion of false information.

Original languageEnglish (US)
Pages (from-to)22-29
Number of pages8
JournalCyberpsychology, Behavior, and Social Networking
Volume20
Issue number1
DOIs
StatePublished - Jan 1 2017

All Science Journal Classification (ASJC) codes

  • Social Psychology
  • Communication
  • Applied Psychology
  • Human-Computer Interaction
  • Computer Science Applications

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