Tope Christopher Falade Data-verified
Affiliation confirmed via AI analysis of OpenAlex, ORCID, and web sources.
Researcher
grad_student
Research Areas
Biography and Research Information
OverviewAI-generated summary
Tope Christopher Falade investigates the intersection of social media, political discourse, and online toxicity. Employing complex network analysis techniques alongside insights from social and intergroup psychology, he seeks to understand and detect hate speech and cyberbullying. His recent work explores generational influences on online toxicity, particularly within the context of health and political discussions. Falade has also developed a neural-symbolic framework leveraging probabilistic soft logic and moral foundations theory to predict toxic intent in online conversations.
His primary research focus is the detection and analysis of online toxicity, with a particular emphasis on the social and psychological factors that contribute to its spread.
Metrics
- h-index: 1
- Publications: 2
- Citations: 2
Selected Publications
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Toxicity-Driven Behavioral Homogenization in Multilayer Political Networks: Cross-Dimensional Coupling During Russia-Ukraine Conflict (2026)
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Weighted Focal Structure Analysis for Coordinated Toxicity Propagation in Social Networks (2026)
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Optimizing Focal Toxic Structure Selection for Social Network Disruption: A WFSA-Integer Programming Approach (2026)
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Large-scale toxicity intervention in social networks: evaluating integer programming-optimized focal toxic structures (2026)
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Modeling Toxicity Propagation in Social Networks with Weighted Focal Structure Analysis and Monte Carlo Epidemic Models (2026)
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Examining Generational Influence in Online Toxicity: Context-Dependent Patterns in Health and Political Discourse (2025)
Collaboration Network
Top Collaborators
- Examining Generational Influence in Online Toxicity: Context-Dependent Patterns in Health and Political Discourse
- Probabilistic Soft Logic for Toxic Intent Prediction in Conversation: a Moral Foundations Theory-Driven Neural-Symbolic Framework