Extraction of Narratives from Podcast Transcripts

Anonymous

Abstract:

\begin{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 media that are growing in popularity, like podcasts, also 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.

\end{abstract}

Paper Type: long

Research Area: Computational Social Science and Cultural Analytics

Contribution Types: NLP engineering experiment, Publicly available software and/or pre-trained models, Data resources, Data analysis

Languages Studied: English

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