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

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...

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Bibliographic Details
Published inNew media & society Vol. 20; no. 1; pp. 272 - 292
Main Authors Liang, Yuhua (Jake), Kee, Kerk F
Format Journal Article
LanguageEnglish
Published London, England SAGE Publications 01.01.2018
Subjects
research strategy
shares
comments
blogs
linguistic analysis
Big data
information diffusion
social media
views
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Summary: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.
ISSN:1461-4448
1461-7315
DOI:10.1177/1461444816661552