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Elenco Pubblicazioni - Publications (1685)

Tessa, B., Cima, L., Trujillo, A., Avvenuti, M., & Cresci, S. (2024). Beyond trial-and-error: Predicting user abandonment after a moderation intervention. Engineering Applications of Artificial intelligence.

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Current content moderation follows a reactive, trial-and-error approach, where interventions are applied and their effects are only measured post-hoc. In contrast, we introduce a proactive, predictive approach that enables moderators to anticipate the impact of…
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Cima, L., Tessa, B., Trujillo, A., Cresci, S., & Avvenuti, M. (2025). Investigating the heterogeneous effects of a massive content moderation intervention via Difference-in-Differences. Online Social Networks and Media, 48, 100320.

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In today's online environments, users encounter harm and abuse on a daily basis. Therefore, content moderation is crucial to ensure their safety and well-being. However, the effectiveness of many moderation interventions is still uncertain. Here,…
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Giorgi, T., Cima, L., Fagni, T., Avvenuti, M., & Cresci, S. Human and LLM biases in hate speech annotations: A socio-demographic analysis of annotators and targets. In Proceedings of the International AAAI Conference on Web and Social Media

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The rise of online platforms exacerbated the spread of hate speech, demanding scalable and effective detection. However, the accuracy of hate speech detection systems heavily relies on human-labeled data, which is inherently susceptible to biases.…
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Cima, L., Miaschi, A., Trujillo, A., Avvenuti, M., Dell'Orletta, F., & Cresci, S. (2025, April). Contextualized counterspeech: Strategies for adaptation, personalization, and evaluation. In Proceedings of the ACM on Web Conference 2025

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AI-generated counterspeech offers a promising and scalable strategy to curb online toxicity through direct replies that promote civil discourse. However, current counterspeech is one-size-fits-all, lacking adaptation to the moderation context and the users involved. We…
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L Gholami, P Ducange, A Gotta, P Cassara,"Cross-Modal Knowledge Distillation for Path Loss Prediction in Urban mmWave UAV-assisted Networks", ICUMT IEEE Conference, 2025

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Accurate path loss (PL) prediction is an essential step for the design and deployment of mmWave UAV-assisted communication networks, especially in urban environments. In this work, we propose a voxel-based 3D Convolutional Neural Network (3D-CNN)…
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