Fake-News Network Model: A Conceptual Framework for Strategic Communication to Deal with Fake News

ABSTRACT

This article analyzes the entire life span of a corporate fake-news report as a case study, proposing a conceptual framework for strategic fake-news communication. Using the confirmation-bias theoretical model, this qualitative textual analysis examines the most widely circulated tweets of a fake-news item about Nike, 603 replies to the tweets, users’ biographical profiles (e.g., political affiliations), the role of opinion leader(s), and relevant prior contexts. The findings provide in-depth insight into how people believe fake news and how their conversations about fake news (re)shape the victim brand’s social realities. Overall, the findings of this study illustrate a “Fake-News Network Model” that explains the underlying mechanisms of how a fake-news item functions together with other aspects (e.g., context, perception, opinion leaders, and cognitive processes), prompting certain people to believe particular fake-news reports and, discuss the victim brand (e.g., Nike) based on that perceived truth. The article discusses the implications of this network model for both fake-news researchers and strategic communication professionals.

Keywords:

• fake news; strategic communication; Nike; confirmation bias; public relations; Twitter; Fake-News Network Model

Acknowledgement

A special thanks to Dr. Carol M. Liebler and Dr. Dennis F. Kinsey, Professors at the S. I. Newhouse School of Public Communications at Syracuse University, for guiding me in this research and reading and commenting on earlier drafts. I also thank Samsunnahar for her help with designing the FNN Model and anonymous reviewers for their insightful comments.

Disclosure statement

The dataset has been used for the first in this article.The research project has not received any funding support, and thearticle has not been published in any other journal.

Data availability statement:

The data that support the findings of this study are available from the author upon reasonable request.

Notes

¹ The fake-news report is available in this archive link: http://archive.fo/1udrr

² This number is not about how large the volume of these tweets is; it simply shows the inclusion of all such tweets in this analysis.