Don’t sleep on it: An examination of storm naming and potential heuristic effects on Twitter

Xialing Lin, Adam M. Rainear, Patric R. Spence, Kenneth A. Lachlan

Research output: Contribution to journalArticle

Abstract

Humans often prefer representations that are cognitively easier to store, and these representations are easier to retrieve later to make judgments about events. Exemplification theory draws on evolutionary logic and argues that simple, iconic, concrete, and emotionally arousing depictions of events (exemplars) are favored and thus more likely to be stored and used than are abstract, inconsequential depictions or representations. This study examined exemplified aspects of storm warnings in a Twitter feed. A three-condition study was completed, and variables examined included storm severity, susceptibility, hazard, outrage, and willingness to change or engage in specific behaviors. Results suggest the possibility of a sleeper effect impacting perceptions of severity. Results are discussed in theoretical and practical applications along with the consideration of other theories to be applied to future research.

Original languageEnglish (US)
Pages (from-to)769-779
Number of pages11
JournalWeather, Climate, and Society
Volume10
Issue number4
DOIs
StatePublished - Oct 2018

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sleep
twitter
heuristics
examination
study conditions
event
hazard
effect

All Science Journal Classification (ASJC) codes

  • Global and Planetary Change
  • Social Sciences (miscellaneous)
  • Atmospheric Science

Cite this

Lin, Xialing ; Rainear, Adam M. ; Spence, Patric R. ; Lachlan, Kenneth A. / Don’t sleep on it : An examination of storm naming and potential heuristic effects on Twitter. In: Weather, Climate, and Society. 2018 ; Vol. 10, No. 4. pp. 769-779.
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Don’t sleep on it : An examination of storm naming and potential heuristic effects on Twitter. / Lin, Xialing; Rainear, Adam M.; Spence, Patric R.; Lachlan, Kenneth A.

In: Weather, Climate, and Society, Vol. 10, No. 4, 10.2018, p. 769-779.

Research output: Contribution to journalArticle

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