IMMENSE: Inductive Multi-perspective User Classification in Social Networks
Online social networks increasingly expose people to users who propagate discriminatory, hateful, and violent content. Young users, in particular, are vulnerable to exposure to such content, which can have harmful psychological and social repercussions. Given the massive scale of today's social networks, in terms of both published content and number of users, there is an urgent need for effective systems to aid Law Enforcement Agencies (LEAs) in identifying and addressing users that disseminate malicious content. In this work we introduce IMMENSE, a machine learning-based method for detecting malicious social network users. Our approach adopts a hybrid classification strategy that integra...
| Authors | Francesco Benedetti, Antonio Pellicani, Gianvito Pio et al. |
|---|---|
| Primary category | cs.SI |
| Published | 5 August 2026 |
| Last updated at source | 5 August 2026 |
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