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Fighting Misinformation, Radicalization and Bias in Social Media

Conference Paper
Publication Date:
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.
Iris type:
04.01 Contributo in Atti di convegno
Keywords:
Bias; Fairness; Fake News Detection; Radicalization
List of contributors:
Manco, Giuseppe; Folino, Gianluigi; Comito, Carmela; Guarascio, Massimo; Pisani, FRANCESCO SERGIO
Authors of the University:
COMITO CARMELA
FOLINO GIANLUIGI
GUARASCIO MASSIMO
MANCO GIUSEPPE
PISANI FRANCESCO SERGIO
Handle:
https://iris.cnr.it/handle/20.500.14243/438351
Book title:
Proceedings of the Italia Intelligenza Artificiale - Thematic Workshops co-located with the 3rd CINI National Lab AIIS Conference on Artificial Intelligence (Ital IA 2023)
Published in:
CEUR WORKSHOP PROCEEDINGS
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URL

https://www.scopus.com/inward/record.uri?eid=2-s2.0-85173823235&partnerID=40&md5=c23ad8a5a7d183aa4124f4dc91dbfb80
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