Our recent research on the role of individuals who do not comply with public health safety measures in epidemic context has been published in the Proceedings of the Royal Society A. The study shows how risky behaviours in case of pandemic and epidemic settings can undermine public health interventions. This is particularly relevant in urban … Continue reading A data-driven analysis of the impact of non-compliant individuals on epidemic diffusion in urban settings
In this study, we present a comprehensive framework for capturing, processing, and analyzing large-scale digital communication data to uncover hidden informal communication patterns within a real-world corporate environment. We run our study on a unique dataset of 40.425.247 email messages exchanged within a banking company, spanning a two-year period. Based on this information, we construct … Continue reading Discovering Hidden Communication Patterns and Informal Organization in Companies through Graph Analysis
We discuss the use of hierarchical transformers for user semantic similarity in the context of analyzing users' behavior and profiling social media users. The objectives of the research include finding the best model for computing semantic user similarity, exploring the use of transformer-based models, and evaluating whether the embeddings reflect the desired similarity concept and can be used for other tasks.
I've been invited to give a keynote talk at the WISE 2022 Conference. Thinking about it, I decided to focus on my idea of a bi-verse. To me, the bi-verse is the duality between the physical and digital worlds. On one side, the Web and social media are the environments where people post their content, … Continue reading Exploring the bi-verse: a trip across the digital and physical ecospheres
Despite the increasing limitations for unvaccinated people, in many European countries, there is still a non-negligible fraction of individuals who refuse to get vaccinated against SARS-CoV-2, undermining governmental efforts to eradicate the virus. Within the PERISCOPE project, we studied the role of online social media in influencing individuals' opinions about getting vaccinated by designing a … Continue reading The VaccinEU dataset of COVID-19 Vaccine Conversations on Twitter in French, German, and Italian
we explored if social media and online review platforms can be a good source of quantitative evaluation of service quality of cultural venues, such as museums, theaters and so on.
Coronavirus COVID-19 is an extreme challenge for our society, economy, and individual life. However, governments should have learnt from each other. The impact has been spreading slowly across countries. There has been plenty of time to take action. But apparently people and government can’t grasp the risk until it’s onto them. And the way European … Continue reading Coronavirus stories and data
Social networks are huge continuous sources of information that can be used to analyze people's behavior and thoughts. Our goal is to extract such information and predict political inclinations of users. In particular, we investigate the importance of syntactic features of texts written by users when they post on social media. Our hypothesis is that … Continue reading Content-based Classification of Political Inclinations of Twitter Users
We exploit the network that builds around the brands by encoding it into a graph model. We build a social network graph, considering user nodes and friendship relations; then we compare it with a heterogeneous graph model.
We implemented an RNN-based analysis that aim to gauge local support for the two major US political parties in the 68 most competitive House of Representative districts during the 2018 U.S. mid-term elections.
