Lucas Maystre, Daniel Russo
Search Mindsets: Understanding Focused and Non-Focused Information Needs in Music Search
Music listening is a commonplace activity that has transformed as users engage with online streaming platforms. When presented with anytime, anywhere access to a vast catalog of music, users face challenges in searching for what they want to hear. We propose that users who engage in domain-specific search (e.g., music search) have different information-seeking needs than in general search. Using a mixed-method approach that combines a large-scale user survey with behavior data analyses, we describe the construct of search mindset on a leading online streaming music platform and then investigate two types of search mindsets: focused, where a user is looking for one thing in particular, and non-focused, where a user is open to different results. Our results reveal that searches in the music domain are more likely to be focused than non-focused. In addition, users’ behavior (e.g., clicks, streams, querying, etc.) on a music search system is influenced by their search mindset. Finally, we propose design implications for music search systems to best support their users.
Challenges in Translating Research to Practice for Evaluating Fairness & Bias in Recommendation Systems
Lex Beattie, Dan Taber, Henriette Cramer
Identifying New Podcasts with High General Appeal Using a Pure Exploration Infinitely-Armed Bandit Strategy
Maryam Aziz, Jesse Anderton, Kevin Jamieson, Alice Wang, Hugues Bouchard, Javed Aslam