Beyond Fake News Detection: A Community-based Study of the Multicultural Nature of Information Disorder
May 1, 2026·,,,,,,,,
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0 min read
Sara Gemelli
Giulia Di Cristina
Yiran Zhang
Md Azizul Hoque
Alberto De La Torre Solís
Mohamad Mojtaba Behboudi Eshkiki
Nikolai Efimov
Mariia Everstova
Caterina Maria Cappello
Maziar Kianimoghadam Jouneghani
Payam Latifi
Yashar Mahboudi
Farzaneh Mohseni
Dario Placenti
Tommaso Caselli
Manuela Sanguinetti
Aurora Scarpellini
Chiara Zanchi
Usman Naseem
Marco Antonio Stranisci
Simona Frenda
Abstract
Recognizing disinformation is a challenging task for humans and AI systems. News can be false, misleading, or harmful, and its interpretation often depends on the cultural context of the audience. However, existing datasets rarely account for these contextual and cultural differences, as they are typically not designed from the perspective of news consumers. To address this gap, in this paper, we present the Information Disorder (InDor) corpus, a multilingual dataset of news articles in English, Farsi, Italian, and Russian, annotated for information disorder detection and explanation. The corpus was developed through a participatory process involving contributors from diverse cultural and professional backgrounds, who engaged in data collection, annotation, and evaluation of Large Language Model (LLM) performance on the task. Our findings highlight that false and manipulated news manifest differently across cultural settings, and that current LLMs fail to adequately capture this complexity. This underscores the need for culturally aware computational approaches in the study of information disorder.
Type
Publication
Proceedings of the Fifteenth Language Resources and Evaluation Conference (LREC 2026)
Authors
PhD Candidate | NLP Researcher
Hi! My name is Maziar, though you can call me Maaz. I’m currently a PhD candidate in Computational Sciences and Technological Innovation, specializing in Artificial Intelligence and Data Science, at the DISIT department, University of Eastern Piedmont (UPO). I’m part of the ARC2S group, working under the supervision of Prof. Giancarlo Ruffo and Prof. Anna Sapienza. I finished my Master’s in Language Technologies and Digital Humanities at the University of Turin in July 2026.
My research over the past two years has centered on multilingual and cross-cultural NLP, and on harmful online content, specifically how it spreads and how it is perceived differently across cultures and communities.
This interest comes from my background. I grew up bilingual in Persian and Qashqai Turkish (a Turkic language of the Oghuz branch), and then did my bachelor’s in English Language Translation, with a focus on linguistics and translation studies. This is the starting point of my interest in meaning, cultures, and languages. We didn’t have interdisciplinary NLP master’s program in my country that I could join with that background (and we still don’t!), so I applied abroad and came to Italy to study NLP.
My master’s thesis, supervised by Prof. Viviana Patti and Dr. Marco Antonio Stranisci, builds on a community-developed dataset on information disorder, InDor. The idea was that an LLM’s fluent reasoning about manipulative content is not necessarily culturally aligned. So I thought maybe retrieving items and explanations from native speakers based on semantic similarity (instead of static few-shot) could fill this gap a bit. I built this retrieval framework and tested it on Persian and Italian, with automatic metrics, a qualitative analysis, and a human evaluation study.
In general, my research interests are: Multilingual & Cross-Cultural NLP, Computational Social Science (CSS), Explainable AI, Fairness, In-Context Learning, Human-in-the-Loop AI, and Information Disorder.
Beyond academia, I spent over 3 years in SEO, web content, and digital marketing.
My research over the past two years has centered on multilingual and cross-cultural NLP, and on harmful online content, specifically how it spreads and how it is perceived differently across cultures and communities.
This interest comes from my background. I grew up bilingual in Persian and Qashqai Turkish (a Turkic language of the Oghuz branch), and then did my bachelor’s in English Language Translation, with a focus on linguistics and translation studies. This is the starting point of my interest in meaning, cultures, and languages. We didn’t have interdisciplinary NLP master’s program in my country that I could join with that background (and we still don’t!), so I applied abroad and came to Italy to study NLP.
My master’s thesis, supervised by Prof. Viviana Patti and Dr. Marco Antonio Stranisci, builds on a community-developed dataset on information disorder, InDor. The idea was that an LLM’s fluent reasoning about manipulative content is not necessarily culturally aligned. So I thought maybe retrieving items and explanations from native speakers based on semantic similarity (instead of static few-shot) could fill this gap a bit. I built this retrieval framework and tested it on Persian and Italian, with automatic metrics, a qualitative analysis, and a human evaluation study.
In general, my research interests are: Multilingual & Cross-Cultural NLP, Computational Social Science (CSS), Explainable AI, Fairness, In-Context Learning, Human-in-the-Loop AI, and Information Disorder.
Beyond academia, I spent over 3 years in SEO, web content, and digital marketing.