143 citations · 295 across the 19 of their papers we have counts for
20 papers
Joint Effects of Recommender Systems and Network Structure on the Visibility of Content and Creators
Virginia Morini, Valentina Pansanella, Luca Pappalardo +2
Social media algorithms allocate users' visibility by ranking content within their social networks. Yet, how recommendation logic and network structure jointly shape visibility acr…
Low-Vocality Engagement Shapes Online Participation
Veronica Mesina, Andrea Failla, Luca Pappalardo +1
Online participation is often measured through visible expression, especially posting, yet many consequential forms of engagement occur through less vocal actions such as liking an…
The Diversity Paradox revisited: Systemic Effects of Feedback Loops in Recommender Systems
Gabriele Barlacchi, Margherita Lalli, Emanuele Ferragina +3
Recommender systems shape individual choices through feedback loops in which user behavior and algorithmic recommendations coevolve over time. The systemic effects of these loops r…
Comparing Explanations is Not Enough, Explain the Change: New Standards are Needed to Explain Behavioral Shifts in Large Language Models
Martino Ciaperoni, Marzio Di Vece, Roberto Pellungrini +3
Large-scale foundation models exhibit behavioral shifts when subjected to interventions such as scaling, fine-tuning, reinforcement learning with human feedback, or in-context lear…
A Simulation Framework for Studying Systemic Effects of Feedback Loops in Recommender Systems
Gabriele Barlacchi, Margherita Lalli, Emanuele Ferragina +2
Recommender systems continuously interact with users, creating feedback loops that shape both individual behavior and collective market dynamics. This paper introduces a simulation…
A computational framework for quantifying route diversification in road networks
Giuliano Cornacchia, Luca Pappalardo, Mirco Nanni +2
The structure of road networks impacts various urban dynamics, from traffic congestion to environmental sustainability and access to essential services. Recent studies reveal that…
Learning by Surprise: Adaptive Mitigation of Model Collapse in Large Language Models
Daniele Gambetta, Gizem Gezici, Fosca Giannotti +3
As AI-generated content increasingly populates the web, generative AI models are at growing risk of being trained on their own outputs, a process known as AI autophagy. This feedba…
The traffic concentration effects of urban navigation services
Giuliano Cornacchia, Mirco Nanni, Dino Pedreschi +1
The collective impact of navigation services remains unclear: while often beneficial to individual drivers, they can unintentionally reshape urban traffic patterns. We simulate the…
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…
Speed Limit: Obey, or Not Obey?
Zhengbing He, Mirco Nanni, Luca Pappalardo +2
It is commonly expected that drivers maintain a driving speed that is lower than or around the posted speed limit, as failure to obey may result in safety risks and fines. By takin…
One-Shot Traffic Assignment with Forward-Looking Penalization
Giuliano Cornacchia, Mirco Nanni, Luca Pappalardo
Traffic assignment (TA) is crucial in optimizing transportation systems and consists in efficiently assigning routes to a collection of trips. Existing TA algorithms often do not a…
Human-AI Coevolution
Dino Pedreschi, Luca Pappalardo, Emanuele Ferragina +14
Human-AI coevolution, defined as a process in which humans and AI algorithms continuously influence each other, increasingly characterises our society, but is understudied in artif…
How Routing Strategies Impact Urban Emissions
Giuliano Cornacchia, Matteo Böhm, Giovanni Mauro +3
Navigation apps use routing algorithms to suggest the best path to reach a user's desired destination. Although undoubtedly useful, navigation apps' impact on the urban environment…
Understanding peacefulness through the world news
Vasiliki Voukelatou, Ioanna Miliou, Fosca Giannotti +1
Peacefulness is a principal dimension of well-being and is the way out of inequity and violence. Thus, its measurement has drawn the attention of researchers, policymakers, and pea…
Modelling Human Mobility considering Spatial,Temporal and Social Dimensions
Giuliano Cornacchia, Giulio Rossetti, Luca Pappalardo
Modelling human mobility is crucial in several areas, from urban planning to epidemic modeling, traffic forecasting, and what-if analysis. On the one hand, existing models focus ma…
The relationship between human mobility and viral transmissibility during the COVID-19 epidemics in Italy
Paolo Cintia, Luca Pappalardo, Salvatore Rinzivillo +29
In 2020, countries affected by the COVID-19 pandemic implemented various non-pharmaceutical interventions to contrast the spread of the virus and its impact on their healthcare sys…
Mobile phone data analytics against the COVID-19 epidemics in Italy: flow diversity and local job markets during the national lockdown
Pietro Bonato, Paolo Cintia, Francesco Fabbri +12
Understanding collective mobility patterns is crucial to plan the restart of production and economic activities, which are currently put in stand-by to fight the diffusion of the e…
Open the Black Box Data-Driven Explanation of Black Box Decision Systems
Dino Pedreschi, Fosca Giannotti, Riccardo Guidotti +4
Black box systems for automated decision making, often based on machine learning over (big) data, map a user's features into a class or a score without exposing the reasons why. Th…
Next Basket Prediction using Recurring Sequential Patterns
Riccardo Guidotti, Giulio Rossetti, Luca Pappalardo +2
Nowadays, a hot challenge for supermarket chains is to offer personalized services for their customers. Next basket prediction, i.e., supplying the customer a shopping list for the…
An analytical framework to nowcast well-being using mobile phone data
Luca Pappalardo, Maarten Vanhoof, Lorenzo Gabrielli +3
An intriguing open question is whether measurements made on Big Data recording human activities can yield us high-fidelity proxies of socio-economic development and well-being. Can…