Program

• 15:00 - 15:05 -- Welcome

• 15:05 - 15:50 -- Keynote: What Do We Need to Effectively Measure Computational Harms? by Alexandra Olteanu

15:50 - 15:55 -- Short break

• 15:55 - 16:15 -- An empirical analysis of recommender systems robustness to shilling attacks (Shrestha, Spezzano, Pera)

• 16:15 - 16:35 -- “To trust a LIAR”: Does Machine Learning really classify fine-grained, Fake News statements? (Mifsud, Layfield, Azzopardi, Abela)

16:35 - 16:50 -- PaRIS: Polarization-aware Recommender Interactive System (Badami, Nasraoui)

• 16:50 - 17:15 -- Break

• 17:15 - 18:00 -- Keynote: Detecting online harmful information: fake news, conspiracy theories and misogyny by Paolo Rosso

18:00 - 18:05 -- Short break

• 18:05 - 18:25 -- User Polarization Aware Matrix Factorization for Recommendation Systems (Sun, Nasraoui)

• 18:25 - 18:45 -- The Privacy versus Disclosure Appetite Dilemma: Mitigation by Recommendation (Ben Salem, Aïmeur, Hage)

• 18:45 - 19:05 -- Adversarial Attacks against Visual Recommendation: an Investigation on the Influence of Items’ Popularity (Anelli, Di Noia, Di Sciascio, Malitesta, Merra)

• 19:05 - 19:10 -- Closing

All times are Amsterdam time.

Presentation times include five minutes (approx) for questions!

Authors will be receiving an email with presentation instructions shortly.