Exploring author gender in book rating and recommendation

@article{Ekstrand2018ExploringAG,
  title={Exploring author gender in book rating and recommendation},
  author={Michael D. Ekstrand and Mucun Tian and Mohammed R. Imran Kazi and Hoda Mehrpouyan and Daniel Kluver},
  journal={Proceedings of the 12th ACM Conference on Recommender Systems},
  year={2018}
}
Collaborative filtering algorithms find useful patterns in rating and consumption data and exploit these patterns to guide users to good items. Many of the patterns in rating datasets reflect important real-world differences between the various users and items in the data; other patterns may be irrelevant or possibly undesirable for social or ethical reasons, particularly if they reflect undesired discrimination, such as gender or ethnic discrimination in publishing. In this work, we examine… Expand
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