Mapping the Podcast Ecosystem with the Structured Podcast Research Corpus

Benjamin Roger Litterer, David Jurgens, Dallas Card


Abstract
Podcasts provide highly diverse content to a massive listener base through a unique on-demand modality. However, limited data has prevented large-scale computational analysis of the podcast ecosystem. To fill this gap, we introduce a massive dataset of over 1.1M podcast transcripts that is largely comprehensive of all English language podcasts available through public RSS feeds from May and June of 2020. This data is not limited to text, but includes metadata, inferred speaker roles, and audio features and speaker turns for a subset of 370K episodes. Using this data, we conduct a foundational investigation into the content, structure, and responsiveness of this ecosystem. Together, our data and analyses open the door to continued computational research of this popular and impactful medium.
Anthology ID:
2025.acl-long.1222
Volume:
Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
Month:
July
Year:
2025
Address:
Vienna, Austria
Editors:
Wanxiang Che, Joyce Nabende, Ekaterina Shutova, Mohammad Taher Pilehvar
Venue:
ACL
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
25132–25154
Language:
URL:
https://preview.aclanthology.org/ingestion-acl-25/2025.acl-long.1222/
DOI:
Bibkey:
Cite (ACL):
Benjamin Roger Litterer, David Jurgens, and Dallas Card. 2025. Mapping the Podcast Ecosystem with the Structured Podcast Research Corpus. In Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), pages 25132–25154, Vienna, Austria. Association for Computational Linguistics.
Cite (Informal):
Mapping the Podcast Ecosystem with the Structured Podcast Research Corpus (Litterer et al., ACL 2025)
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PDF:
https://preview.aclanthology.org/ingestion-acl-25/2025.acl-long.1222.pdf