Spoke 2:
Disinformazione e Fake News (UNISA)

Coordinator:
Vincenzo LOIA
Full Professor, UNISA

Questa AT mira a progettare e sviluppare soluzioni innovative per identificare e gestire le minacce al sistema informativo che si manifestano attraverso le fake news e la loro diffusione. Queste azioni malevole, sfruttando il bias cognitivi delle persone, generano sfiducia dei cittadini nei media e nelle istituzioni. Il progetto utilizzerà un approccio multidisciplinare tramite l’analisi automatica delle notizie liberamente disponibili i recenti progressi dell’Intelligenza Artificiale e le conoscenze delle scienze politiche e geopolitiche. In primo luogo, il progetto mira a verificare la veridicità dei contenuti delle notizie e l’affidabilità delle fonti. L’obiettivo è implementare metodologie di analisi dei contenuti testuali e multimediali per mettere a punto modelli da utilizzare per individuare i tentativi di disinformazione. Inoltre, l’analisi delle comunità dei social media darà evidenza delle vulnerabilità cognitive dei partecipanti e delle minacce legate alla diffusione di fake news. L’obiettivo è quello di progettare un sistema di allerta precoce per mettere in guardia su informazioni false, sfruttando l’integrità sintattica dei contenuti e i modelli legati ai flussi di disinformazione. Il framework risultante punterà a sensibilizzare le persone sugli effetti rischiosi della condivisione di contenuti discutibili. Inoltre, il framework supporterà gli esperti e i responsabili della sicurezza nel processo decisionale, adottando un approccio human-in-the-loop.

Project: DEcision supporT SystEm foR cybeR intelligENCE (DETERRENCE)
PI: Maurizio TESCONI, First-level Researcher, CNR

Project Detection of Deep Fake Media and Life-Long Media Authentication (FF4ALL)
PI: Rocco DE NICOLA, Full Professor, IMT

Project Holistic sUpports against inforMAtioN disordEr (HUMANE)
PI: Fabrizio SILVESTRI, Full Professor, UNIROMA1

Project: Information Disorder Awareness (IDA)
PI: Vincenzo LOIA, Full Professor, UNISA

  • Amendola, M., Cavaliere, D., De Maio, C., Fenza, G., & Loia, V. (2024). Towards Echo Chamber Assessment by employing Aspect-based Sentiment Analysis and GDM Consensus metrics. Online Social Networks and Media. 2024, Journal
  • Alipour, S., Di Marco, N., Avalle, M., Etta, G., Cinelli, M., & Quattrociocchi, W. (2024). The drivers of global news spreading patterns. Scientific Reports, 14(1), 1519. 2024.
  • Di Marco, N., Brunetti, S., Cinelli, M., & Quattrociocchi, W. (2024). Post-hoc evaluation of nodes influence in information cascades: the case of coordinated accounts. arXiv preprint arXiv:2401.01684. 2024 arXiv Preprint
  • Edoardo Di Paolo, Marinella Petrocchi, Angelo Spognardi (2024). Detection of AI-powered bots using image classification. Submitted, HKS Misinformation Review.
  • John Bianchi, Manuel Pratelli, Marinella Petrocchi, Fabio Pinelli (2024). Evaluating Trustworthiness of Online News Publishers via Article Classification. Accepted, ACM SAC 2024. Partner: IMT, CNR
  • Manuel Pratelli, Fabio Saracco, Marinella Petrocchi (2024). Unveiling News Publishers Trustworthiness Through Social Interactions. Accepted, ACM WebSci 2024.
  • Marinella Petrocchi, Marco Viviani. Overview of ROMCIR 2023: The 3rd Workshop on Reducing Online Misinformation through Credible Information Retrieval, ECIR (3) 2023: 405-411
  • Marinella Petrocchi & Marco Viviani. Proceedings of the 3rd Workshop on Reducing Online Misinformation through Credible Information Retrieval 2023 co-located with the 45th European Conference on Information Retrieval (ECIR 2023), Dublin, Ireland, April 2, 2023. CEUR Workshop Proceedings 3406
  • Baqir, A., Galeazzi, A., Zollo, F. News and misinformation consumption: a temporal comparison across European countries.
  • Manuel Pratelli, Fabio Saracco, Marinella Petrocchi (2024). Entropy-based Detection of Twitter Echo Chambers, 1st round of review, PNAS NEXUS, 2024.
  • Manuel Pratelli, Marinella Petrocchi, Fabio Saracco, Rocco De Nicola: Online disinformation in the 2020 U.S. Election: swing vs. safe states. 1st round of review, EPJ Data science, 2024. Partner: IMT, CNR
  • Francesco Amoretti, Introduzione. La Geopolitica della disinformazione, on “Comunicazione politica, Quadrimestrale dell’Associazione Italiana di Comunicazione Politica” 2/2023, pp. 157-174, doi: 10.3270/108042
  • Nicola Capuano, Giuseppe Fenza, Vincenzo Loia, Francesco David Nota: Content-Based Fake News Detection With Machine and Deep Learning: a Systematic Review. Neurocomputing 530: 91-103 (2023)
  • Giuseppe Fenza, Vincenzo Loia, Paola Montserrat Mainardi, Claudio Stanzione: OSINT Knowledge Graph for Fact-Checking: Google Map Hacks Debunking. ITASEC 2023
  • Micaela Bangerter, Giuseppe Fenza, Mariacristina Gallo, Vincenzo Loia, Alberto Volpe, Carmen De Maio, and Claudio Stanzione. 2023. Unisa at SemEval-2023 Task 3: A SHAP-based method for Propaganda Detection. In Proceedings of the 17th International Workshop on Semantic Evaluation (SemEval-2023), pages 885–891, Toronto, Canada. Association for Computational Linguistics.
  • N. Capuano, G. Fenza, V. Loia and C. Stanzione, Explainable Artificial Intelligence in CyberSecurity: A Survey, in IEEE Access, vol. 10, pp. 93575-93600, 2022, doi: 10.1109/ACCESS.2022.3204171.
  • D. Cavaliere, M. Gallo, C. Stanzione, Propaganda Detection Robustness through Adversarial Attacks driven by eXplainable AI, the 1st World Conference on eXplainable Artificial Intelligence (xAI 2023), July 26-28 2023, Lisbon, Portugal
  • Capuano, N., Fenza, G., Gallo, M., Loia, V., Stanzione, C., Unfolding the Misinformation spread: An In-Depth Analysis through Explainable Link Predictions and Data Mining. In International Conference on Intelligence Systems Design and Applications (2023, December) (in press)
  • Fenza, G., Gallo, M., Loia, V., Petrone, A., & Stanzione, C. (2023). Concept-drift detection index based on fuzzy formal concept analysis for fake news classifiers. Technological Forecasting and Social Change, 194, 122640.
  • Becattini, F., Bisogni, C., Loia, V., Pero, C., & Hao, F. (2023). Head Pose Estimation Patterns as Deepfake Detectors. ACM Transactions on Multimedia Computing, Communications and Applications. https://doi.org/10.1145/3612928
  • Gaeta, A., Loia, V., & Orciuoli, F. (2023). An explainable prediction method based on Fuzzy Rough Sets, TOPSIS and Hexagons of opposition: applications to the analysis of Information Disorder. Information Sciences, 120050.
  • Gaeta, A., Orciuoli, F., & Pascuzzo, A. (2023). Satiric Content Detection Through Linguistic Features. In Machine Learning and Artificial Intelligence (pp. 114-119). IOS Press.
  • Damiano, E., Gaeta, A., & Orciuoli, F. (2023, August). Selecting a
    Reduced Set of Features for Supporting the Stance Detection Task. In International Conference on Intelligent Networking and Collaborative Systems (pp. 125-135). Cham: Springer Nature Switzerland.”
  • Luisa Gargano and Adele A. Rescigno. An FPT Algorithm for Spanning Trees with Few Branch Vertices Parameterized by Modular-Width. In Proceedings of 48th International Symposium on Mathematical Foundations of Computer Science (MFCS 2023). Editors: Jérôme Leroux, Sylvain Lombardy, and David Peleg. LIPIcs series; volume: 272; Article No. 50; pp. 50:1–50:15; 2023.
  • Capuano, N., Fenza, G., Gallo, M., Loia, V., Stanzione, C., Unfolding the Misinformation spread: An In-Depth Analysis through Explainable Link Predictions and Data Mining. In International Conference on Intelligence Systems Design and Applications (2023, December) (in press)
  • J. Gao, S. Concas, G. Orrù, X. Feng, G.L. Marcialis, F. Roli, Generalized Deepfake Detection Algorithm based on Inconsistency between Inner and Outer Faces, IAPR Int. Conf. on Image Analysis and Processing (ICIAP 2023), Work. on Recent Advances in Digital Security: Biometrics and Forensics (BIOFOR 2023), Udine (Italy), Sept. 11th, 2023, in press.
  • Marinella Petrocchi, Marco Viviani: ROMCIR 2023: Overview of the 3rd Workshop on Reducing Online Misinformation Through Credible Information Retrieval. ECIR (3) 2023: 405-411
  • Edoardo Di Paolo, Marinella Petrocchi, Angelo Spognardi: From Online Behaviours to Images: A Novel Approach to Social Bot Detection. International Conference on Computational Science ICCS (1) 2023: 593-607″
  • Manuel Pratelli, Marinella Petrocchi, Fabio Saracco, Rocco De Nicola: Swinging in the States: Does disinformation on Twitter mirror the US presidential election system? WWW (Companion Volume) 2023: 1395-1403
  • Marinella Petrocchi, Marco Viviani: Proceedings of the 3rd Workshop on Reducing Online Misinformation through Credible Information Retrieval 2023 co-located with The 45th European Conference on Information Retrieval (ECIR 2023), Dublin, Ireland, April 2, 2023. CEUR Workshop Proceedings 3406, CEUR-WS.org 2023
  • Papa, L., Faiella, L., Corvitto, L., Maiano, L. and Amerini, I., 2023, April. On the use of Stable Diffusion for creating realistic faces: from generation to detection. In 2023 11th International Workshop on Biometrics and Forensics (IWBF) (pp. 1-6). IEEE.
  • Bonaventura, T.S., Maiano, L., Papa, L. and Amerini, I., 2023, June. An Automated Ground-to-Aerial Viewpoint Localization for Content Verification. In 2023 24th International Conference on Digital Signal Processing (DSP) (pp. 1-5). IEEE.
  • Muhammad Imran, Hassaan Khaliq Qureshi, Irene Amerini, BHAC-MRI: Backdoor & Hybrid Attacks on MRI Brain Tumor Classification Using CNN, Image Analysis and Processing – ICIAP 2023
  • Wani, T.M., Amerini, I. (2023). Deepfakes Audio Detection Leveraging Audio Spectrogram and Convolutional Neural Networks. In: Foresti, G.L., Fusiello, A., Hancock, E. (eds) Image Analysis and Processing – ICIAP 2023. ICIAP 2023. Lecture Notes in Computer Science, vol 14234. Springer, Cham. https://doi.org/10.1007/978-3-031-43153-1_14
  • C. Schiavella, L. Cirillo, L. Papa, P. Russo, I. Amerini Optimize ViT architecture via efficient attention modules, in Computer Vision for Environment Monitoring and Preservation (CVEMP) workshop at International Conference on Image Analysis and Processing (ICIAP), 2023
  • Bruni, V., Marconi, S., Monteverde, G., Vitulano, D., Radon transform of image monotonic rearrangements as feature for noise sensor signature, Applied Mathematics and Computation, vol. 457, 2023
  • Coccomini, D.A.; Caldelli, R.; Falchi, F.; Gennaro, C. On the Generalization of Deep Learning Models in Video Deepfake Detection. J. Imaging 2023, 9, 89. https://doi.org/10.3390/jimaging9050089
  • Roberto Caldelli. 2023. Multimedia Forensics versus disinformation in images and videos: lesson learnt and new challenges. In Proceedings of the 2nd ACM International Workshop on Multimedia AI against Disinformation (MAD ’23). Association for Computing Machinery, New York, NY, USA, 2. https://doi.org/10.1145/3592572.3596489
  • AIMH Lab Approaches for Deepfake Detection, Davide Alessandro Coccomini, Roberto Caldelli, Andrea Esuli, Fabrizio Falchi, Claudio Gennaro, Nicola Messina, Giuseppe Amato, Proceedings of the Italia Intelligenza Artificiale – Thematic Workshops (Ital-IA2023)
  • Pantea Nadimi Goki, Stella Civelli, Emanuele Parente, Roberto Caldelli, Thomas Teferi Mulugeta, Nicola Sambo, Marco Secondini, and Luca Potì, Optical identification using physical unclonable functions, J. Opt. Commun. Netw. 15, E63-E73 (2023)
  • Giorgio Barnabò, Federico Siciliano, Carlos Castillo, Stefano Leonardi, Preslav Nakov, Giovanni Da San Martino, Fabrizio Silvestri. Deep active learning for misinformation detection using geometric deep learning. Online Soc. Networks Media 33: 100244 (2023)
  • Giovanni Trappolini, Andrea Santilli, Emanuele Rodolà, Alon Halevy, Fabrizio Silvestri. Multimodal Neural Databases. SIGIR 2023
  • S. Concas, G. Perelli, G.L. Marcialis, G. Puglisi, Tensor-based deepfake detection in scaled and compressed images, 29th IEEE Int. Conf. on Image Processing (ICIP 2022), 16-19 October, 2022, Bordeaux (France), pp. 3121-3125, DOI: 10.1109/ICIP46576.2022.9897606.
  • Serra, A., Carrara, F., Tesconi, M., & Falchi, F. (2023). The Emotions of the Crowd: Learning Image Sentiment from Tweets via Cross-modal Distillation. arXiv preprint arXiv:2304.14942.
  • Gambini, M., Tardelli, S., & Tesconi, M. (2023). The Anatomy of Conspirators: Unveiling Traits using a Comprehensive Twitter Dataset. arXiv preprint arXiv:2308.15154.
  • Cola, G., Mazza, M., & Tesconi, M. (2023). From Tweet to Theft: Tracing the Flow of Stolen Cryptocurrency. CEUR Workshop
  • Coccomini, D. A., Caldelli, R., Falchi, F., & Gennaro, C. (2023). On the Generalization of Deep Learning Models in Video Deepfake Detection. Journal of Imaging, 9(5), 89.
  • Carmela Comito, Francesco Sergio Pisani, Erica Coppolillo, Angelica Liguori, Massimo Guarascio and Giuseppe Manco. Towards Self-Supervised Cross-Domain Fake News Detection. ITASEC 2023
  • Erica Coppolillo, Carmela Comito, Marco Minici, Ettore Ritacco, Gianluigi Folino, Francesco Sergio Pisani, Massimo Guarascio, Giuseppe Manco: Fighting Misinformation, Radicalization and Bias in Social Media. Ital-IA 2023: 443-448
  • Carmela Comito: How Do We Talk and Feel About COVID-19? Sentiment Analysis of Twitter Topics. BigData 2023: 95-107
  • Rosario Catelli, Serena Pelosi, Carmela Comito, Clara Pizzuti, Massimo Esposito, Lexicon-based sentiment analysis to detect opinions and attitude towards COVID-19 vaccines on Twitter in Italy, Computers in Biology and Medicine, Volume 158, 2023, 106876, ISSN 0010-4825
  • Comito, C., Caroprese, L. & Zumpano, E. Multimodal fake news detection on social media: a survey of deep learning techniques. Soc. Netw. Anal. Min. 13, 101 (2023)
  • Biondi, Elisabetta, Chiara Boldrini, Andrea Passarella, and Marco Conti. Dynamics of opinion polarization. IEEE Transactions on Systems, Man, and Cybernetics: Systems (2023).
  • Gambini, M., Avvenuti, M., Falchi, F., Tesconi, M., & Fagni, T. (2023). Detecting Generated Text and Attributing Language Model Source with Fine-tuned Models and Semantic Understanding (2023)
  • Coccomini, D. A., Caldelli, R., Esuli, A., Falchi, F., Gennaro, C., Messina, N., & Amato, G. (2023). AIMH Lab Approaches for Deepfake Detection. In Proceedings of Ital-IA 2023.
    Carmela Comito. Exploring COVID-19 Discourse: Analyzing Sentiments for Fake News Detection in Twitter Topics. In ASONAM 23
  • Caviglione, L., Comito, C., Guarascio, M., Manco, G., Pisani, F. S., & Zuppelli, M. (2023). ORISHA: Improving Threat Detection through Orchestrated Information Sharing – SEBD 2023: 31st Symposium on Advanced Database System, July 02–05, 2023,(Discussion Paper).
  • Khairova, N., Ivasiuk, B., Scudo, F. L., Comito, C., & Galassi, A. (2023, September). A First Attempt to Detect Misinformation in Russia-Ukraine War News through Text Similarity. In Proceedings of the 4th Conference on Language, Data and Knowledge (pp. 559-564).
  • Michele Mazza, Guglielmo Cola, Maurizio Tesconi, Modularity-based approach for tracking communities in dynamic social networks,
    Knowledge-Based Systems, Volume 281, 2023 ISSN 0950-7051, https://doi.org/10.1016/j.knosys.2023.111067.
  • Falkenberg, M., Zollo, F., Quattrociocchi, W., Pfeffer, J., & Baronchelli, A. (2023). Affective and interactional polarization align across countries. arXiv preprint arXiv:2311.18535.
  • Loru, E., Cinelli, M., Tesconi, M., & Quattrociocchi, W. (2023). The influence of coordinated behavior on toxicity. arXiv preprint arXiv:2310.01283.
  • Monti, C., Cinelli, M., Valensise, C., Quattrociocchi, W. & Starnini, M. (2023) Online conspiracy communities are more resilient to deplatforming, PNAS Nexus, Volume 2, Issue 10.
  • Santoro, A. et al. (2023). Analyzing the changing landscape of the Covid-19 vaccine debate on Twitter. Social Network Analysis and Mining, 13(1), 115.
  • Siciliano, F., Maiano, L., Papa, L., Baccini, F., Amerini, I. & Silvestri, F. (2023). Adversarial data poisoning for fake news detection: how to make a model misclassify a target news without modifying it. Workshop on Deep Learning and Multimedia Forensics. Combating fake media and disinformation, ECML-PKDD Workshop 2023 (Accepted for publication).
  • Valensise, C. M., Cinelli, M., & Quattrociocchi, W. (2023). The drivers of online polarization: Fitting models to data. Information Sciences, 642, 119152.
  • Di Paolo E., Bassetti E., Spognardi A. 2023. A New Model for Testing IPv6 Fragment Handling. ESORICS 2023.
  • J. Gao, S. Concas, G. Orrù, X. Feng, G.L. Marcialis, F. Roli, Generalized Deepfake Detection Algorithm based on Inconsistency between Inner and Outer Faces, IAPR Int. Conf. on Image Analysis and Processing (ICIAP 2023), Work. on Recent Advances in Digital Security: Biometrics and Forensics (BIOFOR 2023), Udine (Italy), Sept. 11th, 2023, Springer LNCS 14365, pp. 343-355, DOI: 10.1007/978-3-031-51023-6_29

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