Recommender popularity controls: An observational study

F. Maxwell Harper

Recommender popularity controls: An observational study

F. Maxwell Harper

Computer Science and Engineering

Research output: Contribution to journal › Conference article › peer-review

Abstract

We describe an observational study of a recommender system that provides users with direct control over their personalization. Specifically, we allow users to tune a movie recommender towards more or less popular content. We report on 14 months of usage, which includes 6,846 users who visited the interface at least once.We find, surprisingly, that the popularity of items a user has interacted with historically is a poor predictor of their use of this interface.

Original language	English (US)
Journal	CEUR Workshop Proceedings
Volume	1905
State	Published - Jan 1 2017
Event	2017 Poster Track of the 11th ACM Conference on Recommender Systems, Poster-Recsys 2017 - Como, Italy Duration: Aug 28 2017 → …

Keywords

Observational study
Popularity
Recommender systems

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title = "Recommender popularity controls: An observational study",

abstract = "We describe an observational study of a recommender system that provides users with direct control over their personalization. Specifically, we allow users to tune a movie recommender towards more or less popular content. We report on 14 months of usage, which includes 6,846 users who visited the interface at least once.We find, surprisingly, that the popularity of items a user has interacted with historically is a poor predictor of their use of this interface.",

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author = "Harper, {F. Maxwell}",

year = "2017",

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journal = "CEUR Workshop Proceedings",

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N2 - We describe an observational study of a recommender system that provides users with direct control over their personalization. Specifically, we allow users to tune a movie recommender towards more or less popular content. We report on 14 months of usage, which includes 6,846 users who visited the interface at least once.We find, surprisingly, that the popularity of items a user has interacted with historically is a poor predictor of their use of this interface.

AB - We describe an observational study of a recommender system that provides users with direct control over their personalization. Specifically, we allow users to tune a movie recommender towards more or less popular content. We report on 14 months of usage, which includes 6,846 users who visited the interface at least once.We find, surprisingly, that the popularity of items a user has interacted with historically is a poor predictor of their use of this interface.

KW - Observational study

KW - Popularity

KW - Recommender systems

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UR - http://www.scopus.com/inward/citedby.url?scp=85029214609&partnerID=8YFLogxK

M3 - Conference article

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SN - 1613-0073

VL - 1905

JO - CEUR Workshop Proceedings

JF - CEUR Workshop Proceedings

Y2 - 28 August 2017

ER -

Recommender popularity controls: An observational study

Abstract

Keywords

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