Developing and validating the A-B-C framework of information diffusion on social media

Yuhua (Jake) Liang, Kerk F. Kee

Research output: Contribution to journalArticlepeer-review

11 Scopus citations


This research addresses the problem of promoting information diffusion, the extent to which information spreads, on social media platforms. Utilizing the number of views, comments, and shares as indicators of diffusion, we developed and validated an original research framework based on the big data approach (using all the blog posts in a university in the year 2013; N = 4120). This A-B-C framework (1) analyzes the textual features of blog posts using linguistic inquiry and word count (Study 1), (2) applies the former results to build message concepts (Study 2), and (3) creates validated instructional material based on message concepts to promote message diffusion among blog readers (Study 3). This framework supports operational strategies for developing strategic and corporate communication material aimed at increasing diffusion.

Original languageEnglish
Pages (from-to)272-292
Number of pages21
JournalNew Media and Society
Issue number1
StatePublished - Jan 1 2018


  • Big data
  • blogs
  • comments
  • information diffusion
  • linguistic analysis
  • research strategy
  • shares
  • social media
  • views


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