Automated Text Analysis for Consumer Research

Ashlee Humphreys, Rebecca Jen-Hui Wang, Eileen FischerEditor and Linda PriceAssociate Editor

Journal of Consumer Research, 2018, vol. 44, issue 6, 1274-1306

Abstract: The amount of digital text available for analysis by consumer researchers has risen dramatically. Consumer discussions on the internet, product reviews, and digital archives of news articles and press releases are just a few potential sources for insights about consumer attitudes, interaction, and culture. Drawing from linguistic theory and methods, this article presents an overview of automated text analysis, providing integration of linguistic theory with constructs commonly used in consumer research, guidance for choosing amongst methods, and advice for resolving sampling and statistical issues unique to text analysis. We argue that although automated text analysis cannot be used to study all phenomena, it is a useful tool for examining patterns in text that neither researchers nor consumers can detect unaided. Text analysis can be used to examine psychological and sociological constructs in consumer-produced digital text by enabling discovery or by providing ecological validity.

Keywords: automated text analysis; computer-assisted text analysis; automated content analysis; computational linguistics (search for similar items in EconPapers)
Date: 2018
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Citations: View citations in EconPapers (77)

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Persistent link: https://EconPapers.repec.org/RePEc:oup:jconrs:v:44:y:2018:i:6:p:1274-1306.

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