Gender Stereotyping’s Influence on the Perceived Competence of Siri and Co.

2020

The crowd against the few: Measuring the impact of expert recommendations

2020

Abstract A large amount of research on recommender systems has focused on improving the accuracy of suggestions in offline settings. However, this focus and the commonly used techniques can lead to a “filter bubble”, severely limiting the diversity of content discovered by users. Several offline studies show that this can be mitigated by using experts for recommendation. In contrast to standard recommender systems, experts are able to generate more diverse recommendations and increase the novelty of given suggestions. They can be used in missing-data or cold-start scenarios and reduce noise in the users' ratings. This paper examines the impact of employed experts' recommendations on user be…