Did They Really Tweet That? Querying Fact-Checking Sites and Politwoops to Determine Tweet Misattribution

TL;DR

This paper develops automated methods to verify the existence and authenticity of tweets by querying fact-checking sites and Politwoops, aiming to combat the spread of fabricated social media screenshots and misattribution disinformation.

Contribution

It introduces software tools for automated web querying of tweets and fact-check sites, and evaluates their effectiveness in retrieving evidence of tweets and verifying their truthfulness.

Findings

Google with site:snopes.com achieved high retrieval accuracy (MRR=0.8667, P@1=0.8667)

Snopes built-in search retrieved relevant articles about half the time (MRR=0.5500, P@1=0.5333)

Tools can assist in detecting fabricated social media screenshots

Abstract

Screenshots of social media posts have become common place on social media sites. While screenshots definitely serve a purpose, their ubiquity enables the spread of fabricated screenshots of posts that were never actually made, thereby proliferating misattribution disinformation. With the motivation of detecting this type of disinformation, we researched developing methods of querying the Web for evidence of a tweet's existence. We developed software that automatically makes search queries utilizing the body of alleged tweets to a variety of services (Google, Snopes built-in search, and Reuters built-in search) in an effort to find fact-check articles and other evidence of supposedly made tweets. We also developed tools to automatically search the site Politwoops for a particular tweet that may have been made and deleted by an elected official. In addition, we developed software to scrape fact-check articles from the sites Reuters.com and Snopes.com in order to derive a ``truth rating" from any given article from these sites. For evaluation, we began the construction of a ground truth dataset of tweets with known evidence (currently only Snopes fact-check articles) on the live web, and we gathered MRR and P@1 values based on queries made using only the bodies of those tweets. These queries showed that the Snopes built-in search was effective at finding appropriate articles about half of the time with MRR=0.5500 and P@1=0.5333, while Google when used with the site:snopes.com operator was generally effective at finding the articles in question, with MRR=0.8667 and P@1=0.8667.