Provider fairness across continents in collaborative recommender systemsOpen Website

2022 (modified: 12 Jan 2022)Inf. Process. Manag. 2022Readers: Everyone
Abstract: Highlights • We assess unfairness for groups of providers belonging to different geo-graphic continents, considering state-of-the-art recommendation models. • We propose a multiclass re-ranking algorithm to introduce provider fairness following a notion of equity that distributes the recommendations according to the representation of the groups in the input data. • We evaluate our algorithm in two recommendation domains and study its effectiveness at producing fair but effective recommendations. Abstract When a recommender system suggests items to the end-users, it gives a certain exposure to the providers behind the recommended items. Indeed, the system offers a possibility to the items of those providers of being reached and consumed by the end-users. Hence, according to how recommendation lists are shaped, the experience of under-recommended providers in online platforms can be affected. To study this phenomenon, we focus on movie and book recommendation and enrich two datasets with the continent of production of an item. We use this data to characterize imbalances in the distribution of the user–item observations and regarding where items are produced (geographic imbalance). To assess if recommender systems generate a disparate impact and (dis)advantage a group, we divide items into groups, based on their continent of production, and characterize how represented is each group in the data. Then, we run state-of-the-art recommender systems and measure the visibility and exposure given to each group. We observe disparities that favor the most represented groups. We overcome these phenomena by introducing equity with a re-ranking approach that regulates the share of recommendations given to the items produced in a continent (visibility) and the positions in which items are ranked in the recommendation list (exposure), with a negligible loss in effectiveness, thus controlling fairness of providers coming from different continents. A comparison with the state of the art shows that our approach can provide more equity for providers, both in terms of visibility and of exposure.
0 Replies

Loading