A tale of two internet news platforms-real vs. Fake: An elaboration likelihood model perspective

Babajide Osatuyi, Jerald Hughes

Research output: Chapter in Book/Report/Conference proceedingConference contribution

15 Scopus citations

Abstract

This paper presents findings from a field analysis of real vs. fake news propagated on the Internet. Elaboration Likelihood Model (ELM) was used as a theoretical framework to investigate information presentation mechanisms used by real and fake content generators to persuade readers. ELM theorizes two routes through which information can inform attitudinal changes: a central route of high cognitive effort, and a peripheral route of low cognitive effort. We hypothesize that fake news sites favor the peripheral route by providing less information overall, and by providing more negative affective cues. Data was gathered from Internet platforms that publish real news and fake news. Results indicate that the amount of information disseminated by fake news platforms is lower than that of reputable platforms. Content analysis reveals that fake news with business impact are typically more negative in their valence compared to real news. Implications of our findings for theory and practice are discussed.

Original languageEnglish (US)
Title of host publicationProceedings of the 51st Annual Hawaii International Conference on System Sciences, HICSS 2018
EditorsTung X. Bui
PublisherIEEE Computer Society
Pages3986-3994
Number of pages9
ISBN (Electronic)9780998133119
StatePublished - 2018
Event51st Annual Hawaii International Conference on System Sciences, HICSS 2018 - Big Island, United States
Duration: Jan 2 2018Jan 6 2018

Publication series

NameProceedings of the Annual Hawaii International Conference on System Sciences
Volume2018-January
ISSN (Print)1530-1605

Conference

Conference51st Annual Hawaii International Conference on System Sciences, HICSS 2018
Country/TerritoryUnited States
CityBig Island
Period1/2/181/6/18

All Science Journal Classification (ASJC) codes

  • Engineering(all)

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