University of Urbino
Department of Communication Sciences, Humanities and International Studies
Fabio Giglietto, PhD, is Professor of Internet Studies at the Department of Communication Sciences, Humanities and International Studies at the University of Urbino Carlo Bo. His research explores the intricate relationships between social systems, media, and digital technologies, with a focus on the theory of information, communication, and society. Professor Giglietto teaches courses such as Generative AI and Media, and Digital Social Network Analysis. He actively participates in professional discussions on platforms like BlueSky (@fabiogiglietto.bsky.social) and Mastodon, addressing topics such as platform policies and research methodologies.
Professor Giglietto's work has been published in leading journals, including the Journal of Communication, Information, Communication & Society, the Journal of Broadcasting and Electronic Media, Social Media + Society, and Social Science Computer Review. His publications have garnered over 2200 citations. His research encompasses social media analysis, computational social science, digital methods, and the study of information disorder. Recent work includes an analysis of Meta's political content reduction policy and its impact on the reach of Italian parliamentarians on Facebook.
Professor Giglietto leads the Mapping Italian News Research Program (MINE), which investigates Italian news media coverage and the impact of social media on Italian elections. He is also involved in the EU-funded Horizon Europe project VERAAI, developing AI-based tools for journalists and fact-checkers to verify multimedia content and combat disinformation, with a focus on detecting coordinated behavior and inauthentic networks. Additionally, he contributes to the EU-funded PROMPT initiative, which addresses disinformation narratives across Europe. His current research interests include coordinated behavior detection, multimodal narratives, and the challenges of social media data access.
Giglietto, F. (2025). "A Pretty Blunt Approach": Meta's Political Content Reduction Policy and Italian Parliamentarians' Facebook Visibility. Center for Open Science. https://doi.org/10.31235/osf.io/8dqag_v2
Giglietto, F. (2025). The State of Social Media Research APIs & Tools in the Digital Service Act Era. Zenodo. https://doi.org/10.5281/zenodo.16269197
Giglietto, F. (2025). Manipolazione dei media ed influenza digitale. Sfide, tecnologie e risposte. .
Giglietto, F. (2025). Viralità. .
Giglietto, F. (2025). "A Pretty Blunt Approach": Meta's Political Content Reduction Policy and Italian Parliamentarians' Facebook Visibility. Center for Open Science. https://doi.org/10.31235/osf.io/8dqag_v1
An EU-funded Horizon Europe project that developed advanced AI-based tools to assist journalists and fact-checkers in verifying multimedia content and combating disinformation. As Work Package 4 leader, I focused on the detection of coordinated behavior and inauthentic networks spreading misleading content.
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An EU-funded initiative focused on detecting and analyzing disinformation narratives across Europe, addressing sensitive issues including the war in Ukraine, LGBTQI+ rights, and European elections through the development of language models, monitoring dashboards, and educational resources for fact-checkers and journalists.
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A research program investigating Italian news media coverage and the impact of social media on Italian elections, leveraging data from Social Science One and grant funding from the Social Science Research Council (SSRC).
Learn moreStudies are exploring the potential for AI, and specifically LLMs, to infer political alignments and influence users. Research indicates that LLMs can infer political alignment from online conversations. Furthermore, another study suggests that perceived political bias in LLMs reduces their persuasive abilities.
Read moreSeveral research papers explore the dynamics of online misinformation and coordinated inauthentic behavior. One study analyzes how Serbia's SNS party utilizes coordinated inauthentic behavior to mimic genuine support. Another examines how elected officials share misinformation online, considering institutional and ideological factors. Additionally, research investigates the amplification of division and political intolerance through electoral misinformation in Brazil.
Read moreRecent publications highlight concerns and considerations surrounding the use of Large Language Models (LLMs) in various contexts. One study emphasizes the necessity of curated context for reliable political fact-checking, even when LLMs are equipped with reasoning and web search capabilities. Another paper critiques the unreflective adoption of LLMs in communication research, urging a more cautious and nuanced approach.
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