"Be Careful; Things Can Be Worse than They Appear": Understanding Biased Algorithms and Users' Behavior Around Them in Rating Platforms.
Motahhare EslamiKristen VaccaroKarrie KarahaliosKevin HamiltonPublished in: ICWSM (2017)
Keyphrases
- learning algorithm
- computationally efficient
- optimization problems
- times faster
- orders of magnitude
- novice users
- user generated content
- computational cost
- collaborative filtering
- user interaction
- machine learning
- user feedback
- user experience
- machine learning algorithms
- theoretical analysis
- user interface
- reinforcement learning
- worst case
- social media
- significant improvement
- recommender systems