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The potential for harm entrenched in mis- and disinformation content, regardless of intentionality, opens space for a new analytical agenda to investigate the weaponization of identity-based features like gender, race, and ethnicity through the lens of violence. Therefore, we lay out the triangle of violence to support new studies aiming to investigate multimedia content, victims, and audiences of false claims.

We used a modified Delphi method to elicit and synthesize experts’ views on disinformation, misinformation, and malign influence (DMMI). In a three-part process, experts first independently generated a range of effective strategies for combatting DMMI, identified the most impactful barriers to combatting DMMI, and proposed areas for future research.

Research on digital misinformation has turned its attention to large language models (LLMs) and their handling of sensitive political topics. Through an AI audit, we analyze how three LLM-powered chatbots (Perplexity, Google Bard, and Bing Chat) generate content in response to the prompts linked to common Russian disinformation narratives about the war in Ukraine.

This article analyzes 62 bills introduced in the Brazilian Chamber of Deputies between 2019–2022 to understand how legislators frame disinformation into different problems and their respective solutions. The timeframe coincides with the administration of right-wing President Jair Bolsonaro. The study shows a tendency from legislators of parties opposed to Bolsonaro to attempt to criminalize the creation and spread of health-related and government-led disinformation.

Using data from a nationally representative survey of 2,036 U.S. adults, we analyze partisan perceptions of the risk disinformation poses to the U.S. government and society, as well as the actors viewed as responsible for and harmed by disinformation. Our findings indicate relatively high concern about disinformation across a variety of societal issues, with broad bipartisan agreement that disinformation poses significant risks and causes harms to several groups.

This research identifies an Indonesian-language Twitter disinformation campaign posting pro-government materials on Indonesian governance in Papua, site of a protracted ethno-nationalist, pro-independence insurgency. Curiously, the campaign does not employ common disinformation tactics such as hashtag flooding or the posting of clickbait with high engagement potential, nor does it seek to build user profiles that would make the accounts posting this material appear as important participants in a debate over Papua’s status.

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.

Drawing on preliminary research about the spread of mis- and disinformation across Asian diasporic communities, we advocate for qualitative research methodologies that can better examine historical, transnational, multilingual, and intergenerational information networks. Using examples of case studies from Vietnam, Taiwan, China, and India, we discuss research themes and challenges including legacies of multiple imperialisms, nationalisms, and geopolitical tensions as root causes of mis- and disinformation; difficulties in data collection due to private and closed information networks, language translation and interpretation; and transnational dimensions of information infrastructures and media platforms.

Despite ongoing discussion of the need for increased regulation and oversight of social media, as well as debate over the extent to which the platforms themselves should be responsible for containing misinformation, there is little consensus on which interventions work to address the problem of influence operations and disinformation campaigns.