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Two-Sided Value-Based Music Artist Recommendation in Streaming Music Services

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Title:Two-Sided Value-Based Music Artist Recommendation in Streaming Music Services
Authors:REN, Jing
Kauffman, Robert
King, Dave
Keywords:Social Media Management in Big Data Era
Digital and Social Media
Artist recommendation, collaborative filtering, external information, streaming music, two-sided value
Date Issued:08 Jan 2019
Abstract:Most work on music recommendations has focused on the consumer side not the provider side. We develop a two-sided value-based approach to music artist recommendation for a streaming music scenario. It combines the value yielded for the music industry and consumers in an integrated model. For the industry, the approach aims to increase the conversion rate of potential listeners to adopters, which produces new revenue. For consumers, it aims to improve their utility related to recommendations they receive. We use one year of listening records for 15,000+ users to train and test the proposed recommendation model on 143 artists. Compared to collaborative filtering, the results show some improvement in recommendation performance by considering both sides’ value in con-junction with other factors, including time, location, external information and listening behavior.
Pages/Duration:10 pages
Rights:Attribution-NonCommercial-NoDerivatives 4.0 International
Appears in Collections: Social Media Management in Big Data Era

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