Debates about echo chambers often assume that exposure across political lines fosters understanding, yet online interactions can reinforce ideological boundaries instead. Analyzing Reddit discussions on U.S. politics, this study examines how cross-party replies reshape engagement and community participation. The findings show that such encounters typically deepen within-group activity rather than bridging divides, revealing the fragile conditions under which opinion change and political integration may occur online.

Agent-based models of opinion formation often rely on repeated simulations to approximate observed collective outcomes, limiting both interpretability and efficiency. This work introduces a likelihood-based estimation approach that directly connects model parameters to data through probabilistic generative modeling, allowing opinions and interactions to be inferred from evidence rather than tuned by trial. By applying it to the bounded-confidence model, the study advances a data-driven understanding of how opinions evolve through social influence.

Explainability defines how people interpret and trust machine learning systems, making it central to the interaction between humans and algorithms. This study introduces an axiomatic benchmark to evaluate whether graph-based explainers faithfully reflect the decision process of the models they interpret. By systematically testing white-box classifiers and real-world networks, it exposes the conditions under which explainers deviate from model logic, offering a rigorous framework for assessing faithfulness and robustness in graph explainability.

Moderation policies aim to reduce harm online, yet banning conspiratorial communities can trigger migration and reformation elsewhere. Comparing users of banned Reddit groups with their counterparts on Voat, this study shows that conspiracy networks reconstruct their social ties and activity levels after deplatforming, sustaining both engagement and toxicity. The results underscore the adaptive resilience of conspiratorial ecosystems, calling for moderation strategies that account for cross-platform behavior.