Understanding news sharing in social media: An explanation from the diffusion of innovations theory

Long Ma, Chei Sian Lee*, Dion Hoe Lian Goh

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

121 Citations (Scopus)

Abstract

Purpose: The purpose of this paper is to draw from the diffusion of innovations theory to explore multi-levels of influences (i.e. individuals, networks, news attributes) on news sharing in social media. Design/methodology/approach: A survey was designed and administered to 309 respondents. Structural equation modelling analysis was conducted to examine the three levels of influential factors. These included self-perceptions of opinion leadership and seeking at the individual level, perceived tie strength and homophily at the network level, and finally, perceived news credibility and news preference at the news attribute level. Findings: The results revealed that the influences of self-perceptions of opinion leadership, perceived tie strength in online networks and perceived preference of online news had significant effects on users' news sharing intention in social media. However, self-perceptions of opinion seeking, homophily, and perceived news credibility were not significant. Originality/value: This is one of the first studies on news sharing in social media that focus on diverse levels of influential factors. In particular, the research suggests the viability of the diffusion of innovations theory to explain this pervasive global phenomenon. Further, the influential factors identified may help to stimulate active participation in social media platforms and ultimately enhance the sustainability of these platforms.

Original languageEnglish
Pages (from-to)598-615
Number of pages18
JournalOnline Information Review
Volume38
Issue number5
DOIs
Publication statusPublished - Jul 7 2014
Externally publishedYes

Bibliographical note

Publisher Copyright:
© Emerald Group Publishing Limited.

ASJC Scopus Subject Areas

  • Information Systems
  • Computer Science Applications
  • Library and Information Sciences

Keywords

  • Diffusion of innovations theory
  • News sharing
  • Social media
  • Structural equation modelling

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