Papers by Elisa Sartori
Insights into using temporal coordinated behaviour to explore connections between social media posts and influence (2025.findings-emnlp)
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Elisa Sartori, Serena Tardelli, Maurizio Tesconi, Mauro Conti, Alessandro Galeazzi, Stefano Cresci, Giovanni Da San Martino
| Challenge: | Political campaigns often use coordinated behaviour to identify communities of users who exhibit similar patterns. |
| Approach: | They analysed messages users were exposed to during the UK 2019 election and compared those received by users who shifted communities with others covering the same topics. |
| Outcome: | The results show that political campaigns often use coordinated behaviour to identify communities of users who exhibit similar patterns. |
CritiSense: Critical Digital Literacy and Resilience Against Misinformation (2026.acl-demo)
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Firoj Alam, Fatema Ahmad, Ali Ezzat Shahroor, Mohamed Bayan Kmainasi, Elisa Sartori, Giovanni Da San Martino, Abul Hasnat, Raian Ali
| Challenge: | a recent study found that social media misinformation is reactive and claim-specific, and can degrade under temporal and cross-lingual/domain shift. |
| Approach: | They present a mobile media-literacy app that builds digital literacy skills through short, interactive challenges with instant feedback. |
| Outcome: | The app is the first multilingual and modular platform to improve digital literacy skills. |
Entity Framing and Role Portrayal in the News (2025.findings-acl)
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Tarek Mahmoud, Zhuohan Xie, Dimitar Iliyanov Dimitrov, Nikolaos Nikolaidis, Purificação Silvano, Roman Yangarber, Shivam Sharma, Elisa Sartori, Nicolas Stefanovitch, Giovanni Da San Martino, Jakub Piskorski, Preslav Nakov
| Challenge: | a dataset of news articles containing 22 fine-grained characters is annotated for entity framing and role portrayal . the dataset includes 1,378 recent news articles in five languages focusing on the Ukraine-Russia War and climate change . |
| Approach: | They propose a multilingual and hierarchical corpus annotated for entity framing and role portrayal in news articles. |
| Outcome: | The proposed dataset includes 1,378 recent news articles in five languages focusing on the Ukraine-Russia War and climate change . the authors report evaluation results on state-of-the-art multilingual transformers and hierarchical zero-shot learning using LLMs at the level of a document, paragraph, and sentence . |
MALicious INTent Dataset and Inoculating LLMs for Enhanced Disinformation Detection (2026.eacl-long)
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Arkadiusz Modzelewski, Witold Sosnowski, Eleni Papadopulos, Elisa Sartori, Tiziano Labruna, Giovanni Da San Martino, Adam Wierzbicki
| Challenge: | Existing studies on intentionality behind disinformation do not address intent behind disinformative agents. |
| Approach: | They propose an intent-augmented reasoning system that integrates intent analysis to mitigate the persuasive impact of disinformation. |
| Outcome: | The proposed corpus is the first human-annotated English corpus to capture disinformation and its malicious intent. |
PolyNarrative: A Multilingual, Multilabel, Multi-domain Dataset for Narrative Extraction from News Articles (2025.acl-long)
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Nikolaos Nikolaidis, Nicolas Stefanovitch, Purificação Silvano, Dimitar Iliyanov Dimitrov, Roman Yangarber, Nuno Guimarães, Elisa Sartori, Ion Androutsopoulos, Preslav Nakov, Giovanni Da San Martino, Jakub Piskorski
| Challenge: | a new dataset of news articles annotated for narratives provides a framework for narrative detection . recurring narratives can propagate with very high velocity across audiences, languages and countries . |
| Approach: | They propose a multilingual dataset annotated for narratives using two-level taxonomies . they define narrative as a recurring, repetitive, overt or implicit claim that promotes a specific interpretation or viewpoint on an ongoing topic . |
| Outcome: | The proposed dataset will foster research in narrative detection and enable new research directions . the authors identify multiple narratives in the same article, and the results are published online . |
NarratEX Dataset: Explaining the Dominant Narratives in News Texts (2025.findings-emnlp)
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Nuno Guimarães, Purificação Silvano, Ricardo Campos, Alipio Jorge, Ana Filipa Pacheco, Dimitar Iliyanov Dimitrov, Nikolaos Nikolaidis, Roman Yangarber, Elisa Sartori, Nicolas Stefanovitch, Preslav Nakov, Jakub Piskorski, Giovanni Da San Martino
| Challenge: | a dataset is created to explain the choice of the dominant narrative in a news article . the dataset is intended to address discourse polarization and propaganda detection . |
| Approach: | They propose a dataset for explaining the choice of the dominant narrative in a news article . the dataset is annotated manually with a dominant narrative and sub-narrative labels . |
| Outcome: | The proposed dataset is designed to explain the choice of the dominant narrative in a news article. |
PropXplain: Can LLMs Enable Explainable Propaganda Detection? (2025.findings-emnlp)
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Maram Hasanain, Md Arid Hasan, Mohamed Bayan Kmainasi, Elisa Sartori, Ali Ezzat Shahroor, Giovanni Da San Martino, Firoj Alam
| Challenge: | Currently, propagandistic content detection studies focus on detection, with little attention given to explanations justifying the predicted label. |
| Approach: | They propose a multilingual explanation-enhanced dataset and an explanation-based LLM to address this issue. |
| Outcome: | The proposed model performs comparably while also generating explanations. |