The reviewed record of science sign in
Pith

arxiv: 2109.08245 · v3 · pith:SGRU3QNB · submitted 2021-09-16 · cs.SI

The 2021 RecSys Challenge Dataset: Fairness is not optional

Reviewed by Pith T0 review T1 audit T2 compute T3 formal T4 kernel pith:SGRU3QNBrecord.jsonopen to challenge →

classification cs.SI
keywords datasetchallengerecsysbiggercontentfairnesstwitterarise
0
0 comments X
read the original abstract

After the success the RecSys 2020 Challenge, we are describing a novel and bigger dataset that was released in conjunction with the ACM RecSys Challenge 2021. This year's dataset is not only bigger (~ 1B data points, a 5 fold increase), but for the first time it take into consideration fairness aspects of the challenge. Unlike many static datsets, a lot of effort went into making sure that the dataset was synced with the Twitter platform: if a user deleted their content, the same content would be promptly removed from the dataset too. In this paper, we introduce the dataset and challenge, highlighting some of the issues that arise when creating recommender systems at Twitter scale.

This paper has not been read by Pith yet.

discussion (0)

Sign in with ORCID, Apple, or X to comment. Anyone can read and Pith papers without signing in.