The impact of language on retweeting during acute natural disasters: uncertainty reduction and language expectancy perspectives

Research output: Contribution to journalArticlepeer-review

11 Citations (Scopus)

Abstract

Purpose: Social media have increasingly gained credibility as information sources in emergencies. Retweeting or resharing nature has made Twitter a popular medium of information dissemination. The purpose of this article is to enhance our understanding of both linguistic style and content properties (i.e. both affective and informational contents) that drives resharing behavior or virality of disaster messages on Twitter. We investigate this issue in the context of natural disaster crisis. Design/methodology/approach: In this study, the authors develop, drawing upon language expectancy and uncertainty reduction theories as an enabling framework, hypotheses about how the language (i.e. style and content) influence resharing behavior. They employ a natural language processing of disaster tweets to examine how the language – linguistic style (concrete and interactive language) and linguistic content (information- and affect-focused language) – affects resharing behavior on Twitter during natural disasters. To examine the effects of both linguistic style and content factors on virality, a series of negative binomial regressions were conducted, particularly owing to the highly skewed count data. Findings: Our analysis of tweets from the 2013 Colorado floods shows that resharing disasters tweets increases with the use of concrete language style during acute emergencies. Interactive language is also positively associated with retweet frequency. In addition, neither positive nor negative emotional tweets drive down resharing during acute crises, while information-focused language content has a significantly positive effect on virality. Practical implications: Agencies for public safety and disaster management or volunteer organizations involved in disseminating crisis and risk information to the public may leverage the impacts of the linguistic style and language content through the lens of our research model. The findings encourage practitioners to focus on the role of linguistic style cues during acute disasters. Specifically, from the uncertainty reduction perspective, using concrete language in the disaster tweets is the expected norm, leading to a higher likelihood of virality. Also, interactively frame disaster tweets are more likely to be diffused to a larger number of people on Twitter. Originality/value: The language that people use offer important psychological cue to their intentions and motivations. However, the role of language on Twitter has largely been ignored in this crisis communication and few prior studies have examined the relationship between language and virality during acute emergencies. This article explains the complex and multifaceted nature of information resharing behavior using a multi-theoretical approach – including uncertainty reduction and language expectancy theory – to understand effects of language style and content cues on resharing behavior in the context of natural crisis events.

Original languageEnglish
Pages (from-to)1501-1519
Number of pages19
JournalIndustrial Management and Data Systems
Volume120
Issue number8
DOIs
Publication statusPublished - Aug 11 2020
Externally publishedYes

Keywords

  • Disaster tweet
  • Information diffusion
  • Language expectancy theory
  • Linguistic style
  • Uncertainty reduction

ASJC Scopus subject areas

  • Management Information Systems
  • Industrial relations
  • Computer Science Applications
  • Strategy and Management
  • Industrial and Manufacturing Engineering

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