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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.
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. 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. 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.
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.
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. 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.
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.
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.
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.
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.
R. Guidotti, Monreale, A., Matwin, S., and Pedreschi, D., Black Box Explanation by Learning Image Exemplars in the Latent Feature Space, in Machine Learning and Knowledge Discovery in Databases, Cham, 2020.
R. Guidotti, Monreale, A., Matwin, S., and Pedreschi, D., Black Box Explanation by Learning Image Exemplars in the Latent Feature Space, in Machine Learning and Knowledge Discovery in Databases, Cham, 2020.
R. Guidotti, Monreale, A., Matwin, S., and Pedreschi, D., Black Box Explanation by Learning Image Exemplars in the Latent Feature Space, in Machine Learning and Knowledge Discovery in Databases, Cham, 2020.
G. Rossetti, Morini, V., and Pollacci, L., Capturing Political Polarization of Reddit Submissions in the Trump Era, in SEBD, 2020.
G. Rossetti, Citraro, S., and Milli, L., Conformity: A Path-Aware Homophily Measure for Node-Attributed Networks, arXiv preprint arXiv:2012.05195, 2020.

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