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Conference Paper
L. Milli and Rossetti, G., Community-Aware Content Diffusion: Embeddednes and Permeability, in International Conference on Complex Networks and Their Applications, 2019.
L. Milli, Rossetti, G., Pedreschi, D., and Giannotti, F., Diffusive Phenomena in Dynamic Networks: a data-driven study, in International Conference on Complex Networks CompleNet, Boston March 5-8 2018, 2018.
L. Milli, Rossetti, G., Pedreschi, D., and Giannotti, F., Information diffusion in complex networks: The active/passive conundrum, in International Workshop on Complex Networks and their Applications, 2017.
G. Rossetti, Milli, L., Rinzivillo, S., Sirbu, A., Pedreschi, D., and Giannotti, F., NDlib: Studying Network Diffusion Dynamics, in IEEE International Conference on Data Science and Advanced Analytics, DSA, Tokyo, 2017.
C. Toccaceli, Milli, L., and Rossetti, G., Opinion Dynamic Modeling of Fake News Perception, in International Conference on Complex Networks and Their Applications, 2020.
L. Milli, Monreale, A., Rossetti, G., Pedreschi, D., Giannotti, F., and Sebastiani, F., Quantification in Social Networks, in International Conference on Data Science and Advanced Analytics (IEEE DSAA'2015), Paris, France, 2015.
L. Milli, Monreale, A., Rossetti, G., Giannotti, F., Pedreschi, D., and Sebastiani, F., Quantification Trees, in 2013 IEEE 13th International Conference on Data Mining, Dallas, TX, USA, December 7-10, 2013, 2013, pp. 528–536.
B. Furletti, Gabrielli, L., Giannotti, F., Milli, L., Nanni, M., and Pedreschi, D., Use of mobile phone data to estimate mobility flows. Measuring urban population and inter-city mobility using big data in an integrated approach, in 47th SIS Scientific Meeting of the Italian Statistica Society, Cagliari , 2014.
Journal Article
L. Milli, Rossetti, G., Pedreschi, D., and Giannotti, F., Active and passive diffusion processes in complex networks, Applied network science, vol. 3, p. 42, 2018.
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.
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.
G. Rossetti, Citraro, S., and Milli, L., Conformity: A Path-Aware Homophily Measure for Node-Attributed Networks, arXiv preprint arXiv:2012.05195, 2020.
G. Rossetti, Milli, L., Giannotti, F., and Pedreschi, D., Forecasting success via early adoptions analysis: A data-driven study, PloS one, vol. 12, p. e0189096, 2017.
G. Rossetti, Milli, L., Rinzivillo, S., Sirbu, A., Pedreschi, D., and Giannotti, F., NDlib: a python library to model and analyze diffusion processes over complex networks, International Journal of Data Science and Analytics, pp. 1–19, 2017.
G. Rossetti, Milli, L., Rinzivillo, S., Sirbu, A., Pedreschi, D., and Giannotti, F., NDlib: a python library to model and analyze diffusion processes over complex networks, International Journal of Data Science and Analytics, vol. 5, pp. 61–79, 2018.
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.