Identifying Narrative Content in Podcast Transcripts

Yosra Abdessamed, Shadi Rezapour, Steven Wilson


Abstract
As one of the oldest forms of human communication, narratives appear across a variety of genres and media. Computational methods have been applied to study narrativity in novels, social media, and patient records, leading to new approaches and insights. However, other types of media are growing in popularity, like podcasts. Podcasts contain a multitude of spoken narratives that can provide a meaningful glimpse into how people share stories with one another.In this paper, we outline and apply methods to process English-language podcast transcripts and extract narrative content from conversations within each episode. We provide an initial analysis of the types of narrative content that exists within a wide range of podcasts, and compare our results to other established narrative analysis tools.Our annotations for narrativity and pretrained models can help to enable future research into narrativity within a large corpus of approximately 100,000 podcast episodes.
Anthology ID:
2024.eacl-long.161
Volume:
Proceedings of the 18th Conference of the European Chapter of the Association for Computational Linguistics (Volume 1: Long Papers)
Month:
March
Year:
2024
Address:
St. Julian’s, Malta
Editors:
Yvette Graham, Matthew Purver
Venue:
EACL
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
2631–2643
Language:
URL:
https://aclanthology.org/2024.eacl-long.161
DOI:
Bibkey:
Cite (ACL):
Yosra Abdessamed, Shadi Rezapour, and Steven Wilson. 2024. Identifying Narrative Content in Podcast Transcripts. In Proceedings of the 18th Conference of the European Chapter of the Association for Computational Linguistics (Volume 1: Long Papers), pages 2631–2643, St. Julian’s, Malta. Association for Computational Linguistics.
Cite (Informal):
Identifying Narrative Content in Podcast Transcripts (Abdessamed et al., EACL 2024)
Copy Citation:
PDF:
https://aclanthology.org/2024.eacl-long.161.pdf
Video:
 https://aclanthology.org/2024.eacl-long.161.mp4