What Twitter learned from the Recsys 2020 Challenge [Michael Bronstein et al.]

‘What Twitter learned from the Recsys 2020 Challenge’ is a blog post authored by Michael Bronstein, Luca Belli, Apoorv Sharma, Yuanpu Xie, Ying Xiao, Dan Shiebler, Max Hansmire, and Wenzhe Shi; published on TowardsDataScience.

The authors describe the RecSys 2020 Challenge that was performed on Twitter data.

[We] describe the dataset and the three winning entries submitted by Nvidia, Learner, and Wantely teams. We try to make general conclusions about the choices that helped the winners achieve their results, notably: most important features; extremely fast experimentation speed for feature selection and model training; adversarial validation for generalisation; use of content features; use of decision trees over neural networks

We hope that these findings will be useful to the wider research community and inspire future research directions in recommender systems.