Genre analysis of movies using a topic model of plot summaries

Matthews, Paul; Glitre, Kathrina

Abstract

Genre plays an important role in the description, navigation, and discovery of movies, but it is rarely studied at large scale using quantitative methods. This allows an analysis of how genre labels are applied, how genres are composed and how these ingredients change, and how genres compare. We apply unsupervised topic modeling to a large collection of textual movie summaries and then use the model's topic proportions to investigate key questions in genre, including recognizability, mapping, canonicity, and change over time. We find that many genres can be quite easily predicted by their lexical signatures and this defines their position on the genre landscape. We find significant genre composition changes between periods for westerns, science fiction and road movies, reflecting changes in production and consumption values. We show that in terms of canonicity, canonical examples are often at the high end of the topic distribution profile for the genre rather than central as might be predicted by categorization theory.

• Journal Article Type: Article
• Acceptance Date: May 11, 2021
• Online Publication Date: May 27, 2021
• Publication Date: 2021-12
• Deposit Date: May 28, 2021
• Publicly Available Date: Nov 12, 2021
• Journal: Journal of the Association for Information Science and Technology
• Electronic ISSN: 2330-1643
• Publisher: Association for Information Science and Technology (ASIS&T)
• Peer Reviewed: Peer Reviewed
• Volume: 72
• Issue: 12
• Pages: 1511-1527
• DOI: https://doi.org/10.1002/asi.24525
• Keywords: genre, film, topic modelling, text analytics, categories, knowledge organisation
• Public URL: https://uwe-repository.worktribe.com/output/7428938
• Publisher URL: https://asistdl.onlinelibrary.wiley.com/doi/10.1002/asi.24525
• Additional Information: Received: 2020-07-24; Accepted: 2021-05-11; Published: 2021-05-27