Automated Text Analysis

Ashlee Humphreys ()
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Ashlee Humphreys: Northwestern University

A chapter in Handbook of Market Research, 2022, pp 633-664 from Springer

Abstract: Abstract The amount of text available for analysis by marketing researchers has grown exponentially in the last two decades. Consumer reviews, message board forums, and social media feeds are just a few sources of data about consumer thought, interaction, and culture. However, written language is filled with complex meaning, ambiguity, and nuance. How can marketing researchers possibly transform this rich linguistic representation into quantifiable data for statistical analysis and modeling? This chapter provides an introduction to text analysis, covering approaches that range from top-down deductive methods to bottom-up inductive methods for text mining. After covering some foundational aspects of text analysis, applications to marketing research such as sentiment analysis, topic modeling, and studying organizational communication are summarized and explored, including a case study of word-of-mouth response to a product launch.

Keywords: Text analysis; computer-assisted text analysis; automated content analysis; content analysis; topic modeling; sentiment analysis; LDA; word-of-mouth (search for similar items in EconPapers)
Date: 2022
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Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-3-319-57413-4_26

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DOI: 10.1007/978-3-319-57413-4_26

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