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Rather than assuming that people are motivated to fact-check, we investigated the process that people go through when and if they encounter political misinformation. Using a digital diary method, we asked 38 participants to collect examples of political misinformation during Australia’s 2025 federal election and explain why they determined it to be misinformation (n = 254).

In today’s digital media environment, emotionally resonant narratives often spread faster and stick more firmly than verifiable facts. This paper explores how emotionally charged communication in online controversies fosters not only widespread engagement but also the participatory nature of misinformation. Through a case study of a K-pop controversy, we show how audiences act not just as consumers but as co-authors of alternative narratives in moments of uncertainty.

What if nearly everything we think we know about misinformation came from just a sliver of the world? When research leans heavily on online studies from a few wealthy nations, we risk drawing global conclusions from local noise. A WhatsApp group of fishermen, a displaced community in a refugee camp, or a bustling market in the Global South are not marginal examples of information environments; such contexts call for an evolution of how we study misinformation.

The development of artificial intelligence (AI) allows rapid creation of AI-synthesized images. In a pre-registered experiment, we examine how properties of AI-synthesized images influence belief in misinformation and memory for corrections. Realistic and probative (i.e., providing strong evidence) images predicted greater belief in false headlines.

Outside China, WeChat is a conduit for translating and circulating English-language information among the Chinese diaspora. Australian domestic political campaigns exploit the gaps between platform governance and national media policy, using Chinese-language digital media outlets that publish through WeChat’s “Official Accounts” feature, to reproduce disinformation from English-language sources.

As language models (LMs) continue to develop, concerns over foreign misinformation through models developed in authoritarian countries have emerged. Do LMs favor their home countries? This study audits four frontier LMs by evaluating their favoritism toward world leaders, then measuring how favoritism propagates into misinformation belief.

What kinds of political content thrive on TikTok during an election year? Our analysis of 51,680 political videos from the 2024 U.S. presidential cycle reveals that toxic and partisan content consistently attracts more user engagement—despite ongoing moderation efforts. Posts about immigration and election fraud, in particular, draw high levels of toxicity and attention.

Following the leadership transition on October 27, 2022, Twitter/X underwent a notable change in platform governance. This study investigates how these changes influenced information quality for registered U.S. voters and the platform more broadly. We address this question by analyzing two complementary datasets—a Twitter panel and a Decahose sample.

State media outlets spread propaganda disguised as news online, prompting social media platforms to attach state-affiliated media tags to their accounts. Do these tags reduce belief in state media misinformation? Previous studies suggest the tags reduce misperceptions but focus on Russia, and current research does not compare these tags with other interventions.