mlsanityData to 7 Oct 2026

Mapping the Podcast Ecosystem with the Structured Podcast Research Corpus

arXiv 2411.07892 ↗First posted 12 Nov 2024cs.CL cs.CYcited by 6

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Abstract (arXiv)

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 rather includes audio features and speaker turns for a subset of 370K episodes, and speaker role inferences and other metadata for all 1.1M episodes. Using this data, we also 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.

Key facts. Cited by 6 papers in the map (data through 7 Oct 2026). Builds on 8 of its 67 references that are in the map. First posted on arXiv 12 Nov 2024.

Builds on

8 of 67 references.

References · 8

  1. 2022Robust Speech Recognition via Large-Scale Weak Supervisioncited by 3,972
  2. 2022POTATO: The Portable Text Annotation Toolcited by 64
  3. 2024Careless Whisper: Speech-to-Text Hallucination Harmscited by 53
  4. 2020Quantifying social organization and political polarization in online platformscited by 30
  5. 2023Just Another Day on Twitter: A Complete 24 Hours of Twitter Datacited by 14
  6. 2015QUOTUS: The Structure of Political Media Coverage as Revealed by Quoting Patternscited by 8
  7. 2021Political Discussion is Abundant in Non-political Subreddits (and Less Toxic)cited by 2
  8. 2023When it Rains, it Pours: Modeling Media Storms and the News Ecosystemcited by 2

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2025: 3; 2026: 3.

6 papers.