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The Computational Media and Politics (COMAP) Lab explores how digital technologies and artificial intelligence are transforming political communication and social science research. We focus on three primary areas: Authoritarian Information Control in the Digital Age, Multimodal Political Communication, and AI for Computational Social Science.
Our research examines how authoritarian regimes adapt information control strategies to algorithm-driven media environments; how political and nonpolitical actors leverage visuals, audio, and videos to shape public opinion and mobilize engagement; and how artificial intelligence and large language models can unlock new possibilities for computational social science research. Through these efforts, we aim to advance scholarship in political communication and computational social science, inform policymaking processes, and contribute to building healthier, more resilient information ecosystems.
Authoritarian Information Control in the Digital Age
Authoritarian Information Control in the Digital Age
Half of the world’s population lives under authoritarian rule, where digital media are tightly controlled. Our research examines how these authoritarian regimes adapt propaganda and censorship to algorithm-driven media environments and how such strategies shape public discourse. Current projects in the lab explore the innovation of propaganda production, the role of social media algorithms in amplifying state messaging, the downstream effects of ditial propaganda, and the limitations of censorship.
Recent Publications:
Lu, Y. (Conditionally Accepted). Performative Propaganda Engagement: How Chinese Celebrity Fandom Engages with State Propaganda on Weibo. Political Communication.
Lu, Y., Pan, J., Xu, X., & Xu, Y. (2025). Decentralized Propaganda in the Era of Digital Media: The Massive Presence of the Chinese State on Douyin. American Journal of Political Science. Online First in May 2023.
Hanley, H. W., Lu, Y., & Pan, J. (2025). Across the firewall: Foreign media’s role in shaping Chinese social media narratives on the Russo-Ukrainian War. Proceedings of the National Academy of Sciences, 122(1), e2420607122.
Number of Chinese-regime-affiliated accounts by level and type on Douyin (Chinese TikTok), figure from Lu et al., AJPS, 2025
Work in Progress:
Lu, Y., Liu, X., & Zhou, C. (Under review). Recommending the State: How Social Media Algorithms Curate State-Created Content in China.
Lu, Y. (Manuscript in preparation). How Fans Engage with State Propaganda through Celebrity Mobilization.
Content categories of major protest events on X/Twitter, figure from Lu and Peng, Political Communication, 2024
Multimodal Political Communication
Multimodal Political Communication
The proliferation of multimodal communication has transformed how political and nonpolitical actors gain visibility, mobilize support, and shape public opinion across authoritarian and democratic contexts. Our work examines the communication processes and effects of multimodal content (e.g., short-form videos, AI-generated images), the spread and influence of multimodal misinformation, and the role of AI-generated content in influencing trust and credibility.
Recent Publications:
Lu, Y., & Peng, Y. (2024). The Mobilizing Power of Visual Media Across Stages of Social-Mediated Protests. Political Communication, 41(4), 531-558.
Peng, Q., Lu, Y., & Peng, Y., Qian, S., Liu X., & Shen, C. (2025). Crafting Synthetic Realities: Examining Visual Realism and Misinformation Potential of Photorealistic AI-Generated Images. In Proceedings of the Extended Abstracts of the CHI Conference on Human Factors in Computing Systems (pp. 1-12).
Work in Progress:
Gaw, F., Lu, Y., & Nisbet, E. (Manuscript in preparation). Mapping the Visual Logic of Social Media Influencers and its Audience Engagement: A Computational Visual Approach.
Peng, Y., Lu, Y., & Lin, C. (Manuscript in preparation). Shifting Screens: Progress and Persistent Gaps in Gender and Racial Representation in U.S. Cinema.
AI for Computational Social Science
AI for Computational Social Science
The rapid growth of AI technologies and the proliferation of multimodal digital data present new opportunities and challenges for social science research. Our lab’s research integrates AI-enabled tools such as large language models to advance computational multimodal analysis, enabling the large-scale study of visual, auditory, and video data for social science inquiries. At the same time, we work to expand computational research in non-English contexts and to address sociopolitical biases introduced by AI and large language models
Spotlight project
Computational Media and Politics Lab
Frances Searle Building
2240 Campus Drive
Evanston, IL 60208
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