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P. Bonato, Cintia, P., Fabbri, F., Fadda, D., Giannotti, F., Lopalco, P. Luigi, Mazzilli, S., Nanni, M., Pappalardo, L., Pedreschi, D., Penone, F., Rinzivillo, S., Rossetti, G., Savarese, M., and Tavoschi, L., Mobile phone data analytics against the COVID-19 epidemics in Italy: flow diversity and local job markets during the national lockdown. 2020.
R. Pellungrini, Pappalardo, L., Simini, F., and Monreale, A., Modeling Adversarial Behavior Against Mobility Data Privacy, IEEE Transactions on Intelligent Transportation SystemsIEEE Transactions on Intelligent Transportation Systems, pp. 1 - 14, 2020.
G. Cornacchia, Rossetti, G., and Pappalardo, L., Modelling Human Mobility considering Spatial, Temporal and Social Dimensions, arXiv preprint arXiv:2007.02371, 2020.
C. Toccaceli, Milli, L., and Rossetti, G., Opinion Dynamic Modeling of Fake News Perception, in International Conference on Complex Networks and Their Applications, 2020.
F. Naretto, Pellungrini, R., Monreale, A., Nardini, F. Maria, and Musolesi, M., Predicting and Explaining Privacy Risk Exposure in Mobility Data, in Discovery Science, Cham, 2020.
F. Naretto, Pellungrini, R., Nardini, F. Maria, and Giannotti, F., Prediction and Explanation of Privacy Risk on Mobility Data with Neural Networks, in ECML PKDD 2020 Workshops, Cham, 2020.
F. Pratesi, Gabrielli, L., Cintia, P., Monreale, A., and Giannotti, F., PRIMULE: Privacy risk mitigation for user profiles, vol. 125, p. 101786, 2020.
P. Cintia, Fadda, D., Giannotti, F., Pappalardo, L., Rossetti, G., Pedreschi, D., Rinzivillo, S., Bonato, P., Fabbri, F., Penone, F., Savarese, M., Checchi, D., Chiaromonte, F., Vineis, P., Guzzetta, G., Riccardo, F., Marziano, V., Poletti, P., Trentini, F., Bella, A., Andrianou, X., Del Manso, M., Fabiani, M., Bellino, S., Boros, S., Urdiales, A. Mateo, Vescio, M. Fenicia, Brusaferro, S., Rezza, G., Pezzotti, P., Ajelli, M., and Merler, S., The relationship between human mobility and viral transmissibility during the COVID-19 epidemics in Italy, arXiv preprint arXiv:2006.03141, 2020.
G. Andrienko, Andrienko, N., Boldrini, C., Caldarelli, G., Cintia, P., Cresci, S., Facchini, A., Giannotti, F., Gionis, A., Guidotti, R., and others, (So) Big Data and the transformation of the city, International Journal of Data Science and Analytics, 2020.
G. Rossetti, Milli, L., Citraro, S., and Morini, V., UTLDR: an agent-based framework for modeling infectious diseases and public interventions, arXiv preprint arXiv:2011.05606, 2020.
R. Guidotti, Monreale, A., and Pedreschi, D., The AI black box Explanation Problem, ERCIM NEWS, pp. 12–13, 2019.
A. Sirbu, Pedreschi, D., Giannotti, F., and Kertész, J., Algorithmic bias amplifies opinion fragmentation and polarization: A bounded confidence model, PloS one, vol. 14, p. e0213246, 2019.
D. Morelli, Rossi, A., Cairo, M., and Clifton, D. A., Analysis of the Impact of Interpolation Methods of Missing RR-intervals Caused by Motion Artifacts on HRV Features Estimations, Sensors, vol. 19, p. 3163, 2019.
B. Qureshi, Kamiran, F., Karim, A., Ruggieri, S., and Pedreschi, D., Causal inference for social discrimination reasoning, Journal of Intelligent Information Systems, pp. 1–13, 2019.
G. Rossetti, Milli, L., and Cazabet, R., CDLIB: a python library to extract, compare and evaluate communities from complex networks, Applied Network Science, vol. 4, p. 52, 2019.
R. Cazabet and Rossetti, G., Challenges in community discovery on temporal networks, in Temporal Network Theory, Springer, 2019, pp. 181–197.
L. Milli and Rossetti, G., Community-Aware Content Diffusion: Embeddednes and Permeability, in International Conference on Complex Networks and Their Applications, 2019.
S. Citraro and Rossetti, G., A complex network approach to semantic spaces: How meaning organizes itself, in SEBD, 2019.
S. Bruestle, Pappalardo, L., and Guidotti, R., Defining Geographic Markets from Probabilistic Clusters: A Machine Learning Algorithm Applied to Supermarket Scanner Data, Available at SSRN 3452058, 2019.
G. Calogiuri, Johansen, P. Foss, Rossi, A., and Thurston, M., Do “girls just wanna have fun”? Participation trends and motivational profiles of women in Norway’s ultimate mass participation ski event, Frontiers in Psychology, vol. 10, p. 2548, 2019.
R. Portocarre Sarmento, Lemos, L., Cordeiro, M., Rossetti, G., and Cardoso, D., DynComm R Package–Dynamic Community Detection for Evolving Networks, arXiv preprint arXiv:1905.01498, 2019.
S. Citraro and Rossetti, G., Eva: Attribute-Aware Network Segmentation, in International Conference on Complex Networks and Their Applications, 2019.
G. Rossetti, Exorcising the Demon: Angel, Efficient Node-Centric Community Discovery, in International Conference on Complex Networks and Their Applications, 2019.
C. Panigutti, Guidotti, R., Monreale, A., and Pedreschi, D., Explaining multi-label black-box classifiers for health applications, in International Workshop on Health Intelligence, 2019.
R. Guidotti, Monreale, A., Giannotti, F., Pedreschi, D., Ruggieri, S., and Turini, F., Factual and Counterfactual Explanations for Black Box Decision Making, IEEE Intelligent Systems, 2019.