CrowdLens: Experimenting with crowd-powered recommendation and explanation

Shuo Chang, Max Harper, Lingfei He, Loren G Terveen

Research output: Chapter in Book/Report/Conference proceedingConference contribution

4 Scopus citations

Abstract

Recommender systems face several challenges, e.g., recommending novel and diverse items and generating helpful explanations. Where algorithms struggle, people may excel. We therefore designed CrowdLens to explore different workflows for incorporating people into the recommendation process. We did an online experiment, finding that: compared to a state-of-the-art algorithm, crowdsourcing workflows produced more diverse and novel recommendations favored by human judges; some crowdworkers produced high-quality explanations for their recommendations, and we created an accurate model for identifying high-quality explanations; volunteers from an online community generally performed better than paid crowdworkers, but appropriate algorithmic support erased this gap. We conclude by reflecting on lessons of our work for those considering a crowdsourcing approach and identifying several fundamental issues for future work.

Original languageEnglish (US)
Title of host publicationProceedings of the 10th International Conference on Web and Social Media, ICWSM 2016
PublisherAAAI press
Pages52-61
Number of pages10
ISBN (Electronic)9781577357582
StatePublished - Jan 1 2016
Event10th International Conference on Web and Social Media, ICWSM 2016 - Cologne, Germany
Duration: May 17 2016May 20 2016

Publication series

NameProceedings of the 10th International Conference on Web and Social Media, ICWSM 2016

Other

Other10th International Conference on Web and Social Media, ICWSM 2016
CountryGermany
CityCologne
Period5/17/165/20/16

Fingerprint Dive into the research topics of 'CrowdLens: Experimenting with crowd-powered recommendation and explanation'. Together they form a unique fingerprint.

  • Cite this

    Chang, S., Harper, M., He, L., & Terveen, L. G. (2016). CrowdLens: Experimenting with crowd-powered recommendation and explanation. In Proceedings of the 10th International Conference on Web and Social Media, ICWSM 2016 (pp. 52-61). (Proceedings of the 10th International Conference on Web and Social Media, ICWSM 2016). AAAI press.