From the 1 of 13 linked papers with an AI index.
13 papers
Contextualized Counterspeech Can Be More Persuasive Than Generic Counterspeech
Lorenzo Cima, Alessio Miaschi, Amaury Trujillo +3
The paper investigates AI‑generated counterspeech that is adapted to the conversation and the target user, showing that lightweight contextual and personalization strategies can im…
The Big Ban Theory: A Pre- and Post-Intervention Dataset of Online Content Moderation Actions
Aldo Cerulli, Lorenzo Cima, Benedetta Tessa +2
Online platforms rely on moderation interventions to curb harmful behavior such as hate speech, toxicity, and the spread of mis- and disinformation. Yet research on the effects and…
A Geometric Analysis of Small-sized Language Model Hallucinations
Emanuele Ricco, Elia Onofri, Lorenzo Cima +2
Hallucinations -- plausible but factually incorrect responses -- pose a major challenge to the reliability of Large Language Models (LLMs), especially in multi-step or agentic sett…
Dark Personality Traits and Online Toxicity: Linking Self-Reports to Reddit Activity
Aldo Cerulli, Benedetta Tessa, Giuseppe La Selva +4
Dark personality traits have long been associated with antisocial and toxic online behaviors, yet their relationship with observable online activity remains unclear. We investigate…
Assessing the Reliability of Persona-Conditioned LLMs as Synthetic Survey Respondents
Erika Elizabeth Taday Morocho, Lorenzo Cima, Tiziano Fagni +2
Using persona-conditioned LLMs as synthetic survey respondents has become a common practice in computational social science and agent-based simulations. Yet, it remains unclear whe…
Beyond Trial-and-Error: Predicting User Abandonment After a Moderation Intervention
Benedetta Tessa, Lorenzo Cima, Amaury Trujillo +2
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 p…