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SOCIAL MEDIA DYNAMICS

We use computational, quantitative, and qualitative approaches to characterize peer influence in the context of opinion dynamics and expression.  In so doing, we hope to gain insight into the mechanisms behind observed phenomena and provide model-based approaches for forecasting and prediction.

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  • X. Wang, E. Carpenetti, B. Desmarais, S. Rajtmajer. Silence and noise: Self-censorship and opinion expression on social media. ACM Conference on Computer-Supported Cooperative Work and Social Computing (CSCW), October 2026.

  • X. Wang, S. Koneru, S. Rajtmajer. The Failed Migration of Academic Twitter: A Case Study of Precocious Adopters. The 20th International AAAI Conference on Web and Social Media (ICWSM), May 2026.

  • C. Griffin, S. Rajtmajer, A. Squicciarini, A. Belmonte. Consensus and Information Cascades in Game-Theoretic Imitation Dynamics with Static and Dynamic Network Topologies. SIAM Journal on Applied Dynamical Systems (SIADS), April 2019.

  • J. Semonsen, C. Griffin, A. Squicciarini, S. Rajtmajer. Opinion Dynamics in the Presence of Increasing Agreement Pressure. IEEE Transactions on Cybernetics. February 2018. 

  • J. Semonsen, C. Griffin, A. Squicciarini, and S. Rajtmajer. Consensus on Social Graphs under Increasing Peer Pressure (Extended Abstract). International Conference on Autonomous Agents and Multiagent Systems (AAMAS), May 2017.

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