7 papers
Illusory Truth or Mere Exposure? Model-Dependent Repetition Effects in LLM-Based Social Media Simulations
Azza Bouleimen, Nicolò Pagan, Anikó Hannák
Generative agent-based models (GABMs) are increasingly used to simulate social media dynamics, including misinformation spread. For such social simulations to be valid proxies of h…
Political Sorting Can Drive AI Models Apart Through User Feedback
Petter Törnberg, Michael Heseltine, Nicolò Pagan +3
Large language models are rapidly becoming an important source of political information. This raises a fundamental question: will AI systems support a shared basis for political kn…
Polarization by Default: Auditing Recommendation Bias in LLM-Based Content Curation
Nicolò Pagan, Christopher Barrie, Chris Andrew Bail +1
Large Language Models (LLMs) are increasingly deployed to curate and rank human-created content, yet the nature and structure of their biases in these tasks remains poorly understo…
Learning to Control Misinformation: a Closed-loop Approach for Misinformation Mitigation over Social Networks
Nicolo' Pagan, Andreas Philippou, Giulia De Pasquale
Modern social networks rely on recommender systems that inadvertently amplify misinformation by prioritizing engagement over content veracity. We present a control framework that m…
The Collective Turing Test: Large Language Models Can Generate Realistic Multi-User Discussions
Azza Bouleimen, Giordano De Marzo, Taehee Kim +5
Large Language Models (LLMs) offer new avenues to simulate online communities and social media. Potential applications range from testing the design of content recommendation algor…
Dynamics of toxic behavior in the Covid-19 vaccination debate
Azza Bouleimen, Nicolò Pagan, Stefano Cresci +2
In this paper, we study the behavior of users on Online Social Networks in the context of Covid-19 vaccines in Italy. We identify two main polarized communities: Provax and Novax.…
User's Reaction Patterns in Online Social Network Communities
Azza Bouleimen, Nicolò Pagan, Stefano Cresci +3
Several one-fits-all intervention policies were introduced by the Online Social Networks (OSNs) platforms to mitigate potential harms. Nevertheless, some studies showed the limited…