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Researchers of foreign and domestic influence operations document tactics that frequently recur in covert propaganda campaigns on social media, including backstopping fake personas with plausible biographies or histories, using GAN-generated images as profile photos, and outsourcing account management to paid organizations.

In this pre-registered experiment, we test the effects of conspiracy cue content in the context of the 2020 U.S. elections. Specifically, we varied whether respondents saw an explicitly stated conspiracy theory, one that was merely implied, or none at all. We found that explicit cues about rigged voting machines increase belief in such theories, especially when the cues target the opposing political party.

There is currently no easy way to discover potentially problematic content on WhatsApp and other end-to-end encrypted platforms at scale. In this paper, we analyze the usefulness of a crowd-sourced tipline through which users can submit content (“tips”) that they want fact-checked.

A wealth of interventions have been devised to reduce belief in fake news or the tendency to share such news. By contrast, interventions aimed at increasing trust in reliable news sources have received less attention. In this article, we show that, given the very limited prevalence of misinformation (including fake news), interventions aimed at reducing acceptance or spread of such news are bound to have very small effects on the overall quality of the information environment, especially compared to interventions aimed at increasing trust in reliable news sources.

When U.S. presidential candidates misrepresent the facts, their claims get discussed across media streams, creating a lasting public impression. We show this through a public performance: the 2020 presidential debates. For every five newspaper articles related to the presidential candidates, President Donald J.

We analyzed community guidelines and official news releases and blog posts from 12 leading social media and messaging platforms (SMPs) to examine their responses to COVID-19 misinformation. While the majority of platforms stated that they prohibited COVID-19 misinformation, the responses of many platforms lacked clarity and transparency.

This article explores the ways in which offline conspiracist material concerned with Covid-19 is presented and structured through a content analysis of The Light, a newspaper produced and distributed by activists in the U.K. Our analysis shows that conspiracy theories related to Covid-19 are included alongside a range of other, non-conspiracist content and that readers encounter these ideas in a format which closely resembles a conventional newspaper.

We examine potential bias in Facebook’s 10-trillion cell URLs dataset, consisting of URLs shared on its platform and their engagement metrics. Despite the unprecedented size of the dataset, it was altered to protect user privacy in two ways: 1) by adding differentially private noise to engagement counts, and 2) by censoring the data with a 100-public-share threshold for a URL’s inclusion.

Despite the ubiquity of images and videos in online news environments, much of the existing research on misinformation and its correction is solely focused on textual misinformation, and little is known about how ordinary users evaluate fake or manipulated images and the most effective ways to label and correct such falsities.

To better understand youth attitudes towards media literacy education on social media, and the opportunities and challenges inherent in such initiatives, we conducted a large-scale analysis of user responses to a recent media literacy campaign on TikTok. We found that reactions to the campaign were mixed, and highly political in nature.