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V. Voukelatou, Pappalardo, L., Gabrielli, L., and Giannotti, F., Estimating countries’ peace index through the lens of the world news as monitored by GDELT, in 2020 IEEE 7th International Conference on Data Science and Advanced Analytics (DSAA)2020 IEEE 7th International Conference on Data Science and Advanced Analytics (DSAA), 2020.
N. Forgó, Hänold, S., van den Hoven, J., Krügel, T., Lishchuk, I., Mahieu, R., Monreale, A., Pedreschi, D., Pratesi, F., and van Putten, D., An ethico-legal framework for social data science, 2020.
R. Cazabet, Boudebza, S., and Rossetti, G., Evaluating community detection algorithms for progressively evolving graphs, arXiv preprint arXiv:2007.08635, 2020.
O. Lampridis, Guidotti, R., and Ruggieri, S., Explaining Sentiment Classification with Synthetic Exemplars and Counter-Exemplars, in Discovery Science, Cham, 2020.
M. Setzu, Guidotti, R., Monreale, A., and Turini, F., Global Explanations with Local Scoring, in Machine Learning and Knowledge Discovery in Databases, Cham, 2020.
A. Sirbu, Andrienko, G., Andrienko, N., Boldrini, C., Conti, M., Giannotti, F., Guidotti, R., Bertoli, S., Kim, J., Muntean, C. Ioana, Pappalardo, L., Passarella, A., Pedreschi, D., Pollacci, L., Pratesi, F., and Sharma, R., Human migration: the big data perspective, International Journal of Data Science and Analytics, pp. 1–20, 2020.
S. Citraro and Rossetti, G., Identifying and exploiting homogeneous communities in labeled networks, Applied Network Science, vol. 5, pp. 1–20, 2020.
R. Guidotti and Rossetti, G., “Know Thyself” How Personal Music Tastes Shape the Last.Fm Online Social Network, in Formal Methods. FM 2019 International Workshops, Cham, 2020.
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.
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.
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.