3 papers
cs.IR2025
A survey on the impacts of recommender systems on users, items, and human-AI ecosystems
Luca Pappalardo, Salvatore Citraro, Giuliano Cornacchia +12
Recommendation systems and assistants (in short, recommenders) influence through online platforms most actions of our daily lives, suggesting items or providing solutions based on…
physics.soc-ph2025
Dynamic models of gentrification
Giovanni Mauro, Nicola Pedreschi, Renaud Lambiotte +1
The phenomenon of gentrification of an urban area is characterized by the displacement of lower-income residents due to rising living costs and an influx of wealthier individuals.…
cs.AI2025
The Urban Impact of AI: Modeling Feedback Loops in Next-Venue Recommendation
Giovanni Mauro, Marco Minici, Luca Pappalardo
Next-venue recommender systems are increasingly embedded in location-based services, shaping individual mobility decisions in urban environments. While their predictive accuracy ha…