Corpus ID: 46860212

All The Cool Kids, How Do They Fit In?: Popularity and Demographic Biases in Recommender Evaluation and Effectiveness

@inproceedings{Ekstrand2018AllTC,
  title={All The Cool Kids, How Do They Fit In?: Popularity and Demographic Biases in Recommender Evaluation and Effectiveness},
  author={Michael D. Ekstrand and Mucun Tian and Ion Madrazo Azpiazu and J. Ekstrand and Oghenemaro Anuyah and David McNeill and M. S. Pera},
  booktitle={FAT},
  year={2018}
}
In the research literature, evaluations of recommender system effectiveness typically report results over a given data set, providing an aggregate measure of effectiveness over each instance (e.g. user) in the data set. Recent advances in information retrieval evaluation, however, demonstrate the importance of considering the distribution of effectiveness across diverse groups of varying sizes. For example, do users of different ages or genders obtain similar utility from the system… Expand
The Impact of Popularity Bias on Fairness and Calibration in Recommendation
Popularity Bias in Recommendation: A Multi-stakeholder Perspective
Multistakeholder recommendation: Survey and research directions
Evaluating content novelty in recommender systems
...
1
2
3
4
5
...

References

SHOWING 1-10 OF 36 REFERENCES
A Comparison of How Demographic Data Affects Recommendation
Evaluating Recommendation Systems
Explaining the user experience of recommender systems
A Survey of Accuracy Evaluation Metrics of Recommendation Tasks
Evaluating collaborative filtering recommender systems
Hybrid Recommender Systems: Survey and Experiments
  • R. Burke
  • Computer Science
  • User Modeling and User-Adapted Interaction
  • 2004
...
1
2
3
4
...