Automated text analyses of YouTube comments as field experiments for assessing consumer sentiment towards products and brands
Journal of Product & Brand Management
ISSN: 1061-0421
Article publication date: 29 September 2021
Issue publication date: 6 June 2022
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
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