Understanding the Use of Fauxtography on Social Media

TL;DR

This study investigates the prevalence and impact of manipulated images, known as fauxtography, in online disinformation, revealing their widespread use and influence on social media engagement.

Contribution

It introduces a novel computational pipeline for detecting fauxtography and provides large-scale analysis of its usage and effects across multiple social media platforms.

Findings

Over 61,000 instances of fauxtography identified

Posts with fauxtography receive more engagement

Fauxtography images are often turned into memes

Abstract

Despite the influence that image-based communication has on online discourse, the role played by images in disinformation is still not well understood. In this paper, we present the first large-scale study of fauxtography, analyzing the use of manipulated or misleading images in news discussion on online communities. First, we develop a computational pipeline geared to detect fauxtography, and identify over 61k instances of fauxtography discussed on Twitter, 4chan, and Reddit. Then, we study how posting fauxtography affects engagement of posts on social media, finding that posts containing it receive more interactions in the form of re-shares, likes, and comments. Finally, we show that fauxtography images are often turned into memes by Web communities. Our findings show that effective mitigation against disinformation need to take images into account, and highlight a number of challenges in dealing with image-based disinformation.