Titlebook: Disinformation in Open Online Media; 5th Multidisciplinar Davide Ceolin,Tommaso Caselli,Marina Tulin Conference proceedings 2023 The Editor

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,FaKy: A Feature Extraction Library to Detect the Truthfulness of a Text,r effectiveness. Textual features have shown their potential to help identify fake news in a transparent manner. In this paper, we survey a list of textual features, evaluate their usefulness in predicting fake news by testing them on a real-world dataset, and collect them in a Python library called

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From Sharing Misinformation to Debunking It: How Coordinated Image Text Sharing Behaviour is Used in posts containing images about Lula da Silva or Jair Bolsonaro, the candidates in the Brazilian run-off election (n = 509,219 Facebook posts). The analysis is based on a script to identify CITSB on Facebook and includes social network analysis and a manual review of the most shared content. Finding

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,Lost in Transformation: Rediscovering LLM-Generated Campaigns in Social Media,arly challenge algorithms focused on the temporal analysis of topical clusters. Simple similarity measures can no longer capture and map campaigns that were previously broadly similar in content. Herein, we analyze whether the classification of messages over time can be profitably used to rediscover

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,Coordinated Information Campaigns on Social Media: A Multifaceted Framework for Detection and Analysocial, political, and economic processes. This paper proposes a multifaceted framework for detecting and analyzing coordinated message promotion on social media. By simultaneously considering features related to content, time, and network dimensions, our framework can capture the diverse nature of

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,ChatGPT as a Commenter to the News: Can LLMs Generate Human-Like Opinions?,been investigated for a wide variety of tasks. In this research we investigate to what extent GPT-3.5 can generate human-like comments on Dutch news articles. We define human likeness as ‘not distinguishable from human comments’, approximated by the difficulty of automatic classification between hum