Rate and review: Exploring listener motivations for engagement with music podcasts

Barber, Simon and Hamilton, Craig (2022) Rate and review: Exploring listener motivations for engagement with music podcasts. Radio Journal: International Studies in Broadcast & Audio Media, 20 (1). pp. 17-32. ISSN 1476-4504

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Abstract

Podcasts have become an important part of music reception practices, providing new ways of engaging with reviews and recommendations, artist interviews and popular music histories. This article presents a replicable working methodology that can be applied to study the data associated with podcasts of any genre. In our analysis, we explore approximately 16,000 listener reviews of the Top 50 podcasts in the Apple (UK) music chart in order to discover what it is about music podcasts that draws listeners to regularly engage with their favourite shows. This method, based on unsupervised machine learning algorithms, automates data-scraping for podcast reviews and ratings. We describe and critically reflect on this process in order to understand not only how listeners describe their range of motivations for engagement with music podcasts, but also the limitations of this approach in a media and cultural studies context.

Item Type:	Article
Identification Number:	10.1386/rjao_00053_1
Dates:	Date Event 3 February 2022 Accepted 1 April 2022 Published Online
Uncontrolled Keywords:	data; digital humanities; machine learning; natural language processing; podcasting; reception
Subjects:	CAH24 - media, journalism and communications > CAH24-01 - media, journalism and communications > CAH24-01-05 - media studies CAH25 - design, and creative and performing arts > CAH25-02 - performing arts > CAH25-02-02 - music
Divisions:	Faculty of Arts, Design and Media > College of English and Media
Depositing User:	Simon Barber
Date Deposited:	16 Dec 2022 09:30
Last Modified:	01 Apr 2023 03:00
URI:	https://www.open-access.bcu.ac.uk/id/eprint/14027

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