485 citations · 915 across the 23 of their papers we have counts for
24 papers
Rewiring What-to-Watch-Next Recommendations to Reduce Radicalization Pathways
Francesco Fabbri, Yanhao Wang, Francesco Bonchi +2
Recommender systems typically suggest to users content similar to what they consumed in the past. If a user happens to be exposed to strongly polarized content, she might subsequen…
Exposure Inequality in People Recommender Systems: The Long-Term Effects
Francesco Fabbri, Maria Luisa Croci, Francesco Bonchi +1
People recommender systems may affect the exposure that users receive in social networking platforms, influencing attention dynamics and potentially strengthening pre-existing ineq…
SciClops: Detecting and Contextualizing Scientific Claims for Assisting Manual Fact-Checking
Panayiotis Smeros, Carlos Castillo, Karl Aberer
This paper describes SciClops, a method to help combat online scientific misinformation. Although automated fact-checking methods have gained significant attention recently, they r…
Predicting Early Dropout: Calibration and Algorithmic Fairness Considerations
Marzieh Karimi-Haghighi, Carlos Castillo, Davinia Hernandez-Leo +1
In this work, the problem of predicting dropout risk in undergraduate studies is addressed from a perspective of algorithmic fairness. We develop a machine learning method to predi…
Perceptions of Diversity in Electronic Music: the Impact of Listener, Artist, and Track Characteristics
Lorenzo Porcaro, Emilia Gómez, Carlos Castillo
Shared practices to assess the diversity of retrieval system results are still debated in the Information Retrieval community, partly because of the challenges of determining what…
A Note on the Significance Adjustment for FA*IR with Two Protected Groups
Meike Zehlike, Tom Sühr, Carlos Castillo
In this report we provide an improvement of the significance adjustment from the FA*IR algorithm of Zehlike et al., which did not work for very short rankings in combination with a…