XBRL diffusion in social media: discourses and community learning

Arif Perdana, Alastair Robb, Fiona Rohde

Research output: Contribution to journalArticleResearchpeer-review

15 Citations (Scopus)

Abstract

Multiple discourses are critical in determining the success of information technology (IT) diffusion. Since its inception, such discourses also appear in the eXtensible Business Reporting Language (XBRL) diffusion sphere. To help explain XBRL diffusion, we explore the discourses relative to XBRL in social media. A case study with text mining and content analysis was conducted to address three research questions covering community discourses, polarity of viewpoint, and learning surrounding XBRL in social media. Our sample data consisted of members’ posts and comments in LinkedIn XBRL groups over the period 2010 to 2013. Our analysis finds that XBRL discourses in social media have largely revolved around the dissemination of XBRL information to raise awareness among potential adopters (i.e., theorization) and to properly implement XBRL (i.e., translation). Our findings indicate that XBRL’s theorization is not in doubt, while XBRL’s translation remains challenging. Professionals generally view XBRL positively. Those who view XBRL less favorably are more likely to be skeptical rather than dismissive. We also observe that social media like LinkedIn is a relevant channel for communities to learn about XBRL. We discuss the findings and include several insights and implications that may be useful in augmenting the future of XBRL.

Original languageEnglish
Pages (from-to)71-106
Number of pages36
JournalThe Journal of Information Systems
Volume29
Issue number2
DOIs
Publication statusPublished - 1 Jun 2015
Externally publishedYes

Keywords

  • Community learning
  • Discourse analysis
  • eXtensible business reporting language
  • Institutional theory
  • IT diffusion
  • LinkedIn
  • Social media
  • XBRL

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