Social media messaging platforms are central to worldwide communication, but are also major hubs of misinformation and toxic content. On these platforms, information spreads through interpersonal and group-based chats rather than feed-based recommendations. We argue that introducing barriers to usage can increase the costs of consuming low-quality content and promote more deliberate engagement, shaping information consumption and downstream attitudes. We evaluate our argument through three coordinated online field experiments in Brazil, India, and South Africa.  We incentivize participants to either avoid multimedia content on WhatsApp or to limit their usage to 10 minutes per day for four weeks ahead of each country's elections. Our interventions significantly reduced participants’ exposure to uncivil political discussions and misinformation---but at the expense of keeping up with political news. However, political attitudes did not shift, although treated participants did report improved well-being, particularly when they substituted WhatsApp usage with more offline activities.

Bio:

Assistant Professor in Computational Social Science at Georgetown University’s McCourt School of Public Policy. Before joining Georgetown, he was a Postdoctoral Fellow at NYU’s Center for Social Media, AI and Politics and a Misinformation Researcher at Twitter. He holds a Ph.D. in Political Science from the University of Maryland, College Park.

His research examines how digital technologies, social media and, more recently, generative AI, shape political information and behavior, with a focus on Global South countries. He has primarily pursued a comparative approach to these issues, paying particular attention to Global South countries and using multi-country large-scale designs to study the intersection of social media and politics. Methodologically, he is interested in survey research in the digital space, large-scale digital experimentation, and the use of large language models in applied social science research.