A workflow for analyzing cultural schemas in texts

Marshall A. Taylor and Dustin S. Stoltz

The Journal of Mathematical Sociology, 2025, vol. 49, issue 1, 1-24

Abstract: Concept class analysis (CoCA) is a method for recovering cultural schemas in texts using a combination of word embedding and community detection models. Like survey-based forms of schematic class analysis (SCA), however, interpreting results can be difficult. Some of these interpretive difficulties are applicable across types of SCA, while others are unique to CoCA. In this paper, we propose a complete workflow for interpreting and analyzing CoCA output. We use the case of social identity schemas in a collection of over 13,000 U.S. political blog posts to outline a number of interpretive and analytical strategies and a robustness check to make sense of the cultural schemas recovered from texts.

Date: 2025
References: Add references at CitEc
Citations:

Downloads: (external link)
http://hdl.handle.net/10.1080/0022250X.2024.2395806 (text/html)
Access to full text is restricted to subscribers.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:taf:gmasxx:v:49:y:2025:i:1:p:1-24

Ordering information: This journal article can be ordered from
http://www.tandfonline.com/pricing/journal/gmas20

DOI: 10.1080/0022250X.2024.2395806

Access Statistics for this article

The Journal of Mathematical Sociology is currently edited by Noah Friedkin

More articles in The Journal of Mathematical Sociology from Taylor & Francis Journals
Bibliographic data for series maintained by Chris Longhurst ().