Here we go! Summary thread of our new paper "Balanced Quality Score (BQS): Measuring Popularity Debiasing in Recommendation" out on ACM TIST!

Excited to share KDD Lab Pisa latest work on Human-AI Coevolution, exploring the intertwined influence between recommenders and humans in social media, online retail, urban mapping, and genAI: 👉 arxiv.org/abs/2306.13723⁣ 👉 arxiv.org/abs/2407.01630…⁣ Dino Pedreschi Emanuele Ferragina

A questo punto il Corriere venne colto da un leggero sospetto

The #EUCommission is kicking off its first round of action against big online platforms, starting with X. Does the EU have what it takes to enforce its rules? How will the new political dynamics in Europe shape this battle?

Our contribution "Link Polarity Prediction from Sparse and Noisy Labels via Multiscale Social Balance" with Federico Cinus Francesco Bonchi Giuseppe Manco has been accepted as a Full Research Paper at #CIKM2024 ACM CIKM 2024

paper alert: "Robust anomaly detection via adversarial counterfactual generation": a semi-supervised anomaly detection and generation method based on adversarial counterfactual reconstruction. Joint work with Angelica Liguori, Ettore Ritacco & F. Pisani link.springer.com/article/10.100…

Preprint alert: GenRec: A Flexible Data Generator for Recommendations. Joint work with Erica Coppolillo @simoneFaber_ Ettore Ritacco. A framework for synthetic user-item interactions that exhibit realistic properties in recommendation scenarios arxiv.org/pdf/2407.16594

Check out Martino Ciaperoni's work "The Hadamard Decomposition Problem." It offers a fresh, original approach to the classic challenge of low-rank approximation, with practical applications in fields such as Computer Vision and Recommendation Systems.

Uncovering Coordinated Cross-Platform Information Operations Threatening the Integrity of the 2024 U.S. Presidential Election Online Discussion w/ Emilio Ferrara Marco Minici Federico Cinus View our findings here: papers.ssrn.com/sol3/papers.cf…