"This is Fake! Shared it by Mistake": Assessing the Intent of Fake News Spreaders

TL;DR

This paper investigates the intent behind fake news spreading, proposing a novel influence graph to distinguish between intentional and unintentional spreaders, and demonstrates that intent assessment improves fake news detection.

Contribution

It introduces the first model to assess individuals' intent in fake news spreading using an influence graph and psychological insights, enhancing detection methods.

Findings

Intent assessment significantly differentiates spreader types

Estimated intent improves fake news detection accuracy

Psychological explanations underpin the influence graph model

Abstract

Individuals can be misled by fake news and spread it unintentionally without knowing it is false. This phenomenon has been frequently observed but has not been investigated. Our aim in this work is to assess the intent of fake news spreaders. To distinguish between intentional versus unintentional spreading, we study the psychological explanations of unintentional spreading. With this foundation, we then propose an influence graph, using which we assess the intent of fake news spreaders. Our extensive experiments show that the assessed intent can help significantly differentiate between intentional and unintentional fake news spreaders. Furthermore, the estimated intent can significantly improve the current techniques that detect fake news. To our best knowledge, this is the first work to model individuals' intent in fake news spreading.