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Automated text analyses of YouTube comments as field experiments for assessing consumer sentiment towards products and brands

Charles S. Areni (Uncommon Sense Marketing Research Pty Ltd, Oyster Bay, Australia and University of Wollongong, Wollongong, Australia)

Journal of Product & Brand Management

ISSN: 1061-0421

Article publication date: 29 September 2021

Issue publication date: 6 June 2022

617

Abstract

Purpose

The purpose of this study is to show how non-random groupings of YouTube videos can be combined with automated text analysis (ATA) of user comments to conduct quasi-experiments on consumer sentiment towards different types of brands in a naturalistic setting.

Design/methodology/approach

NCapture extracted thousands of comments on multiple videos representing different experimental treatments and Leximancer revealed differences in the lexical patterns of user comments for different types of brands.

Findings

User comments consistently revealed hypothesized relationships between brand types, based on existing theory regarding motivations for nostalgia and the relationship between consumer preferences, online product ratings and purchases. These results demonstrate the viability of conducting quasi-experimental research in naturalistic settings via non-random groupings of YT videos and ATA of user comments.

Research limitations/implications

This research adopts a single quasi-experimental design: the non-equivalent group, after-only design. However, the same basic approach can be used with other quasi-experimental designs to examine different kinds of research questions.

Originality/value

Overall, this research points to the potential for ATA of comments on different categories of YT videos as a relatively straightforward approach for conducting field experiments that establish the ecological validity of laboratory findings. The method is easy to use and does not require the participation and cooperation of private, third party social media research companies.

Keywords

Acknowledgements

On behalf of all authors, the corresponding author states that there is no conflict of interest and no external funding sources contributed to this research.

Citation

Areni, C.S. (2022), "Automated text analyses of YouTube comments as field experiments for assessing consumer sentiment towards products and brands", Journal of Product & Brand Management, Vol. 31 No. 5, pp. 702-717. https://doi.org/10.1108/JPBM-01-2021-3341

Publisher

:

Emerald Publishing Limited

Copyright © 2021, Emerald Publishing Limited

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