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2022
M. Fontana, Naretto, F., Monreale, A., and Giannotti, F., “Monitoring Fairness in HOLDA”, in HHAI 2022: Augmenting Human Intellect - Proceedings of the First International Conference on Hybrid Human-Artificial Intelligence, Amsterdam, The Netherlands, 13-17 June 2022, 2022.
L. Corbucci, Monreale, A., Panigutti, C., Natilli, M., Smiraglio, S., and Pedreschi, D., “Semantic Enrichment of XAI Explanations for Healthcare”, 24th International Conference on Artificial Intelligence. 2022.
R. Trasarti, Grossi, V., Natilli, M., and Rapisarda, B., “SoBigData++: European Integrated Infrastructure for Social Mining and Big Data Analytics.”, 30th Italian Symposium on Advanced Database Systems (SEBD – Sistemi Evoluti per Basi di Dati). Tirrenia, Pisa, 2022.
R. Guidotti, Monreale, A., Ruggieri, S., Naretto, F., Turini, F., Pedreschi, D., and Giannotti, F., “Stable and actionable explanations of black-box models through factual and counterfactual rules”, Data Mining and Knowledge Discovery, 2022.
2021
F. Bodria, Giannotti, F., Guidotti, R., Naretto, F., Pedreschi, D., and Rinzivillo, S., “Benchmarking and Survey of Explanation Methods for Black Box Models”, CoRR, vol. abs/2102.13076, 2021.
S. Marina Joseph, Citraro, S., Morini, V., Rossetti, G., and Stella, M., “Cognitive network science quantifies feelings expressed in suicide letters and Reddit mental health communities”, arXiv preprint arXiv:2110.15269, 2021.
G. Rossetti, Citraro, S., and Milli, L., “Conformity: a Path-Aware Homophily measure for Node-Attributed Networks”, IEEE Intelligent SystemsIEEE Intelligent Systems, pp. 1 - 1, 2021.
F. Lillo and Ruggieri, S., “Estimating the Total Volume of Queries to a Search Engine”, IEEE Transactions on Knowledge and Data Engineering, pp. 1-1, 2021.
F. Giannotti, Naretto, F., and Bodria, F., “Explainable for Trustworthy AI”, in Human-Centered Artificial Intelligence - Advanced Lectures, 18th European Advanced Course on AI, ACAI 2021, Berlin, Germany, October 11-15, 2021, extended and improved lecture notes, 2021.
L. Pappalardo, Rossi, A., Natilli, M., and Cintia, P., “Explaining the difference between men’s and women’s football”, PLOS ONE, vol. 16, p. e0255407, 2021.
M. Nanni, Andrienko, G., Barabasi, A. - L., Boldrini, C., Bonchi, F., Cattuto, C., Chiaromonte, F., Comandé, G., Conti, M., Coté, M., Dignum, F., Dignum, V., Domingo-Ferrer, J., Ferragina, P., Giannotti, F., Guidotti, R., Helbing, D., Kaski, K., Kertész, J., Lehmann, S., Lepri, B., Lukowicz, P., Matwin, S., Jiménez, D. Megías, Monreale, A., Morik, K., Oliver, N., Passarella, A., Passerini, A., Pedreschi, D., Pentland, A., Pianesi, F., Pratesi, F., Rinzivillo, S., Ruggieri, S., Siebes, A., Torra, V., Trasarti, R., van den Hoven, J., and Vespignani, A., “Give more data, awareness and control to individual citizens, and they will help COVID-19 containment”, 2021.
M. Setzu, Guidotti, R., Monreale, A., Turini, F., Pedreschi, D., and Giannotti, F., “GLocalX - From Local to Global Explanations of Black Box AI Models”, vol. 294, p. 103457, 2021.
L. Pappalardo, Grossi, V., and Pedreschi, D., “Introduction to the special issue on social mining and big data ecosystem for open, responsible data science”, 2021.
G. Cornacchia and Pappalardo, L., “A Mechanistic Data-Driven Approach to Synthesize Human Mobility Considering the Spatial, Temporal, and Social Dimensions Together”, ISPRS International Journal of Geo-Information, vol. 10, p. 599, 2021.
M. Fontana, Naretto, F., and Monreale, A., “A new approach for cross-silo federated learning and its privacy risks”, in 18th International Conference on Privacy, Security and Trust, PST 2021, Auckland, New Zealand, December 13-15, 2021, 2021.
M. Fontana, Naretto, F., and Monreale, A., “A new approach for cross-silo federated learning and its privacy risks”, in 2021 18th International Conference on Privacy, Security and Trust (PST), 2021.
G. Mariani, Monreale, A., and Naretto, F., “Privacy Risk Assessment of Individual Psychometric Profiles”, in Discovery Science - 24th International Conference, DS 2021, Halifax, NS, Canada, October 11-13, 2021, Proceedings, 2021.
G. Cornacchia and Pappalardo, L., “STS-EPR: Modelling individual mobility considering the spatial, temporal, and social dimensions together”, 2021.
V. Morini, Pollacci, L., and Rossetti, G., “Toward a Standard Approach for Echo Chamber Detection: Reddit Case Study”, Applied Sciences, vol. 11, p. 5390, 2021.
V. Lorenzoni, Triulzi, I., Martinucci, I., Toncelli, L., Natilli, M., Barale, R., and Turchetti, G., “Understanding eating choices among university students: A study using data from cafeteria cashiers’ transactions”, Health Policy, vol. 125, pp. 665–673, 2021.
2020
M. Natilli, Fadda, D., Rinzivillo, S., Pedreschi, D., and Licari, F., “Analysis and Visualization of Performance Indicators in University Admission Tests”, in Formal Methods. FM 2019 International Workshops, Cham, 2020.
G. Rossetti, “ANGEL: efficient, and effective, node-centric community discovery in static and dynamic networks”, Applied Network Science, vol. 5, pp. 1–23, 2020.
D. Pedreschi and Miliou, I., “Artificial Intelligence (AI): new developments and innovations applied to e-commerce”, European Parliament's committee on the Internal Market and Consumer Protection, 2020.
B. Dong, Wang, H., Monreale, A., Pedreschi, D., Giannotti, F., and Guo, W., “Authenticated Outlier Mining for Outsourced Databases”, IEEE Transactions on Dependable and Secure Computing, vol. 17, pp. 222 - 235, 2020.
E. Ntoutsi, Fafalios, P., Gadiraju, U., Iosifidis, V., Nejdl, W., Vidal, M. - E., Ruggieri, S., Turini, F., Papadopoulos, S., Krasanakis, E., and others, “Bias in data-driven artificial intelligence systems—An introductory survey”, Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery, vol. 10, p. e1356, 2020.

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