Podcast Metadata and Content: Episode Relevance and Attractiveness in Ad Hoc Search

Published

July 11, 2021

Author(s)

Ian Soboroff, Ben Carterette, Rosie Jones, Gareth Jones, Maria Eskevich, Sravana Reddy, Ann Clifton, Yongze Yu, Jussi Karlgren

Abstract

Rapidly growing online podcast archives contain diverse content on a wide range of topics. These archives form an important resource for entertainment and professional use, but their value can only be realized if users can rapidly and reliably locate content of interest. Search for relevant content can be based on metadata provided by content creators, but also on transcripts of the spoken content itself. Excavating relevant content from deep within these audio streams for diverse types of information needs requires varying the approach to systems prototyping. We describe a set of diverse podcast information needs and different approaches to assessing retrieved content for relevance. We use these information needs in an investigation of the utility and effectiveness of these information sources. Based on our analysis, we recommend approaches for indexing and retrieving podcast content for ad hoc search.

Proceedings Title

Proceedings of SIGIR 2021

Conference Dates

July 11-15, 2021

Conference Location

Virtual Event, CA

Conference Title

Association for Computing Machinery (ACM) Special Interest Group on Information Retrieval (SIGIR)

Pub Type

Conferences

Download Paper

Local Download

Keywords

information retrieval, podcasts

Citation

Soboroff, I. , Carterette, B. , Jones, R. , Jones, G. , Eskevich, M. , Reddy, S. , Clifton, A. , Yu, Y. and Karlgren, J. (2021), Podcast Metadata and Content: Episode Relevance and Attractiveness in Ad Hoc Search, Proceedings of SIGIR 2021, Virtual Event, CA, [online], https://tsapps.nist.gov/publication/get_pdf.cfm?pub_id=932343 (Accessed March 14, 2025)