Research topics

My research mainly focuses on the analysis of Big Data, especially those coming from the main social media platforms, which provide a massive amount of opinion-rich multi-modal data effectively exploitable for extracting valuable information about users’ dynamics, behavior, and opinion. In particular, the scope of my research is twofold: one the one hand to develop innovative methodologies and algorithms for the analysis of Big Social Data; on the other hand to design and implement novel techniques to enable their efficient execution in high-performance distributed environments.
I produced several interesting results in both research directions mentioned above, in a wide range of application domains, including: political event analysis, opinion mining, polarization and emotion analysis, topic detection and tracking, and hashtag recommendation. I also investigated how polarization analysis techniques can be combined with information diffusion and influence maximization models, how to effectively learn from poorly supervised datasets, and how to use machine learning for optimizing the execution of data-intensive applications.