Curtailing Fake News Propagation with Psychographics

36 Pages Posted: 15 Apr 2020 Last revised: 23 Nov 2020

See all articles by Hani Safadi

Hani Safadi

University of Georgia; University of Georgia - C. Herman and Mary Virginia Terry College of Business

Weifeng Li

University of Georgia

Saber Soleymani

University of Georgia

Ugur Kursuncu

University of South Carolina - Artificial Intelligence Institute

Amit Sheth

Wright State University - Ohio Center of Excellence in Knowledge-Enabled Computing (Kno.e.sis)

Date Written: January 1, 2020

Abstract

Fake news is a widespread and concerning phenomenon. The goal of this article is twofold. First, we argue that curtailing fake news is better pursued by identifying its propagators than by classifying its content. Second, to validate our conceptual argument, we develop a system for curtailing the propagation of fake news on social media by identifying users who are susceptible to believing and propagating it. We anchor our approach in the debate about the ontological nature of truth, the empirical challenges of classifying fake news content, as well as the psychological and social origins of believing fake news. Through interpreting our model using modern explainable machine learning, we deepen our theoretical understanding of why people believe and share fake news, extend the applicability of our system beyond its original context, and provide guidelines for mitigating fake news propagation.

Keywords: fake news, psychographics, explainable machine learning, social media

JEL Classification: M15

Suggested Citation

Safadi, Hani and Li, Weifeng and Soleymani, Saber and Kursuncu, Ugur and Sheth, Amit, Curtailing Fake News Propagation with Psychographics (January 1, 2020). Available at SSRN: https://ssrn.com/abstract=3558236 or http://dx.doi.org/10.2139/ssrn.3558236

Hani Safadi (Contact Author)

University of Georgia ( email )

Athens, GA 30602-6254
United States

University of Georgia - C. Herman and Mary Virginia Terry College of Business ( email )

Brooks Hall
Athens, GA 30602-6254
United States

Weifeng Li

University of Georgia ( email )

610 S. Lumpkin St.
Benson C404
Athens, GA 30602
United States

Saber Soleymani

University of Georgia ( email )

Athens, GA 30602-6254
United States

Ugur Kursuncu

University of South Carolina - Artificial Intelligence Institute ( email )

701 Main Street
Columbia, SC 29208
United States

Amit Sheth

Wright State University - Ohio Center of Excellence in Knowledge-Enabled Computing (Kno.e.sis)

Dayton, OH 45435
United States

Here is the Coronavirus
related research on SSRN

Paper statistics

Downloads
140
Abstract Views
707
rank
237,795
PlumX Metrics