Social media have become the ideal place for black hats and malicious individuals to target susceptible users through different attack vectors and then manipulate their opinions and interests. Fake news, radicalization, and pushing bias into the data represent some popular ways noxious users adopt to perpetrate their criminal intents. In this evolving scenario, Artificial Intelligence techniques represent a valuable tool to early detect and mitigate the risk due to the spreading of these emerging attacks. In this work, we describe the Machine Learning based solutions developed to address the problems mentioned above and our current research.

Fighting Misinformation, Radicalization and Bias in Social Media

Carmela Comito;Gianluigi Folino;Francesco Sergio Pisani;Massimo Guarascio;Giuseppe Manco
2023

Abstract

Social media have become the ideal place for black hats and malicious individuals to target susceptible users through different attack vectors and then manipulate their opinions and interests. Fake news, radicalization, and pushing bias into the data represent some popular ways noxious users adopt to perpetrate their criminal intents. In this evolving scenario, Artificial Intelligence techniques represent a valuable tool to early detect and mitigate the risk due to the spreading of these emerging attacks. In this work, we describe the Machine Learning based solutions developed to address the problems mentioned above and our current research.
2023
Istituto di Calcolo e Reti ad Alte Prestazioni - ICAR
Bias
Fairness
Fake News Detection
Radicalization
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.14243/438351
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