At the Society Complexity and Data Science Laboratory (CDCS Lab), our primary objective is to harness the power of data science to tackle a diverse array of challenges. These range from understanding the spread of information on social media platforms to developing models for epidemic outbreaks, and analyzing mobility trends.

We firmly believe in the synergy of network science and complex systems, utilizing this blend to construct mathematical models of intricate dynamics. It's through this integrated approach that we unravel large-scale, pivotal phenomena.


The drivers of online polarization: fitting models to data
Online users often form echo chambers within polarized groups, reinforcing shared narratives. This phenomenon arises from human biases in information consumption and personalized recommendations by feed algorithms. While previous studies have explored these dynamics using opinion dynamic models, empirical validation and qualitative analysis have been limited. This work proposes a method to numerically compare simulated opinion distributions with real social media data. We develop an opinion dynamic model that considers the interplay between human and algorithmic factors, validated against diverse social media platforms. By providing a synthetic description of social media characteristics, our research contributes to refining feed algorithms and mitigating extreme polarization's detrimental effects on online discourse.

Team (Academic Children) 


Matteo Cinelli, Researcher- Data-Driven Modeling of Social Dynamics - Sapienza Alessandro Galeazzi, PostDoc - Data-Driven Modeling of Social Dynamics - Ca'FoscariGabriele Etta, Ph.D Candidate - Data-Driven Modeling of Social Dynamics  - Sapienza
Niccolò Di Marco, Ph. D. Candidate - Data-Driven Modeling of Social Dyanmics - Università di Firenze
Michele Avalle, PostDoc - Data-Driven Modeling of Social Dynamics - Sapienza
Saverio Storani, PostDoc - Data-Driven Modeling of Social Dynamics - Sapienza
Lorenzo Alvisi, PreDoc - Data-Driven Modeling of Social Dynamics - Sapienza
Anita Bonetti, PreDoc - Meme Dynamics - Sapienza
Emanuele Sangiorgio, Ph.D Candidate - Collective Memory in Online Dynamics - Sapienza
Shayan Alipour, Ph.D Candidate- The Interplay between meme and news - Sapienza
Edoardo Di Martino, MA Thesis: Toxicity and Polarization Dynamics
Edoardo Loru, MA Thesis, Toxicity and Coordinated Inauthentic Behavior
Giulio Pecile, MA Thesis, Models and Algorithms for Modeling Social Dynamics
Simon Zollo, MA Thesis, Political Opinion Inference from Twitter


Carlo Valensise, PostDoc - Information Spreading and Memes Evolution - Centro FermiEmanuele Brugnoli, PostDoc - Information Spreading PatternsAntonio Peruzzi, Ph.D - Economic Impact of NewsAna Lucia Schmidt. (Supervisor) News spreading on a global scale, IMT LuccaAlessandro Bessi. (Supervisor) Quantitative understanding of online misinformation, IUSS Pavia.Michela Del Vicario. (Supervisor) Data driven modeling of social contagion, IMT LuccaFabiana Zollo. (Supervisor) Sensing social dynamics in the misinformation era, IMT Lucca