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From Big Data to Rich Theory: Integrating Critical Discourse Analysis with Structural Topic Modeling
Author(s) -
Aranda Ana M.,
Sele Kathrin,
Etchanchu Helen,
Guyt Jonne Y.,
Vaara Eero
Publication year - 2021
Publication title -
european management review
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.784
H-Index - 32
eISSN - 1740-4762
pISSN - 1740-4754
DOI - 10.1111/emre.12452
Subject(s) - legitimation , sociology , epistemology , critical discourse analysis , data science , topic model , management science , computer science , big data , political science , artificial intelligence , data mining , engineering , philosophy , politics , ideology , law
A growing interest in the study of discourses has spread in management research, but so far, it has mostly relied on in‐depth qualitative analyses of textual material. With the increasing availability of large textual data, several challenges arise. This paper offers a mixed‐methods approach to integrate critical discourse analysis with structural topic modeling to turn these challenges into valuable opportunities. We argue that combining both approaches overcomes their limitations and provides great potential for exploring phenomena that matter in our mediatized society. Based on an explanatory sequential mixed‐methods design, we develop a stepwise model that provides practical and theoretical guidance to conduct a critical analysis of large textual data. Our illustrative example focuses on the discursive legitimation struggles around the tobacco industry. We demonstrate how an integrated mixed‐methods approach allows capturing the breadth and depth of discourses used by different actors in the tobacco debates.