443 citations · 1.4k across the 18 of their papers we have counts for
19 papers
Uncovering the Sociodemographic Fabric of Reddit
Federico Cinus, Corrado Monti, Paolo Bajardi +1
Understanding the sociodemographic composition of online platforms is essential for accurately interpreting digital behavior and its societal implications. Yet, current methods oft…
Moral Judgments in Online Discourse are not Biased by Gender
Lorenzo Betti, Paolo Bajardi, Gianmarco De Francisci Morales
The interaction between social norms and gender roles prescribes gender-specific behaviors that influence moral judgments. Here, we study how moral judgments are biased by the gend…
Streamlining models with explanations in the learning loop
Francesco Lomuscio, Paolo Bajardi, Alan Perotti +1
Several explainable AI methods allow a Machine Learning user to get insights on the classification process of a black-box model in the form of local linear explanations. With such…
Learning Multiscale Non-stationary Causal Structures
Gabriele D'Acunto, Gianmarco De Francisci Morales, Paolo Bajardi +1
This paper addresses a gap in the current state of the art by providing a solution for modeling causal relationships that evolve over time and occur at different time scales. Speci…
Revealing the determinants of gender inequality in urban cycling with large-scale data
Alice Battiston, Ludovico Napoli, Paolo Bajardi +4
Cycling is an outdoor activity with massive health benefits, and an effective solution towards sustainable urban transport. Despite these benefits and the recent rising popularity…
GRAPHSHAP: Explaining Identity-Aware Graph Classifiers Through the Language of Motifs
Alan Perotti, Paolo Bajardi, Francesco Bonchi +1
Most methods for explaining black-box classifiers (e.g. on tabular data, images, or time series) rely on measuring the impact that removing/perturbing features has on the model out…