Spread of Risk Information Through Microblogs: Twitter Users with More Mutual Connections Relay News That is More Dreadful

Masashi Komori, Asako Miura, Naohiro Matsumura, Kai Hiraishi, Kazutoshi Maeda

Research output: Contribution to journalArticle

Abstract

In elucidating the spread of risk information through microblogging, it is important to understand the behaviors of numerous average users, in addition to the activities of authorities. We followed the transmission pathways of 10 actual widely spread tweets concerning several risk information topics, including natural disasters, nuclear disasters, and infectious diseases, and we identified the types of risk that affected retweeting by classifying each tweet based on Slovic's risk-perception model. Furthermore, we examined the types of users who did and did not retweet the information. Users with few connections in the form of followers (i.e., people who are following a user) or followees (people a user is following), or with a low ratio of mutual followers within their connections, had a tendency to retweet a large amount of risk information, regardless of the type of risk involved. On the other hand, users with a high ratio of mutual followers exhibited a greater tendency to retweet risk information when it was perceived as dreadful, though they did not retweet risk information much on the whole. These results suggest that there are two mechanisms by which risk information is spread within the Twitter network: information exchange and social sharing of personal reactions.

Original languageEnglish
JournalJapanese Psychological Research
DOIs
Publication statusAccepted/In press - 2019 Jan 1

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Disasters
Information Services
Social Support
Communicable Diseases

Keywords

  • microblog
  • personal network
  • retweet
  • risk information
  • risk perception

ASJC Scopus subject areas

  • Psychology(all)

Cite this

Spread of Risk Information Through Microblogs : Twitter Users with More Mutual Connections Relay News That is More Dreadful. / Komori, Masashi; Miura, Asako; Matsumura, Naohiro; Hiraishi, Kai; Maeda, Kazutoshi.

In: Japanese Psychological Research, 01.01.2019.

Research output: Contribution to journalArticle

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