JAR Inside the Research Podcast
This podcast gives listeners a look at the latest research articles published in the Journal of Advertising Research. Listen to authors describe their work and what motivated it, explore challenges they faced in the research process, and describe what they'd like to researched next.
JAR Inside the Research Podcast
Consumer Responses to LGBTQ-Themed Advertising: What 20,000 YouTube Comments Reveal
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In this episode, guest interviewer Dr. Steven Park (Queen Mary University of London) speaks with Jia Heng Li and Professor Tae Hyun Baek (both Sungkyunkwan University) to discuss their article, "Consumer Responses to LGBTQ-Themed Advertising: A Computational Analysis of YouTube Comments," coauthored with Minseong Kim (Louisiana State University Shreveport), just published in the June 2026 issue of JAR.
Jia Heng explains how the study moves beyond the surveys and experiments that dominate research on LGBTQ-themed advertising by analyzing what consumers naturally say online. Using computational text mining of more than 20,000 YouTube comments on LGBTQ-themed ads, the authors identify six key topics of conversation, from LGBTQ celebrations and family values to drag culture, brand activism, and gender roles. The headline finding is that overall sentiment is more positive than many might expect, with themes of pride, inclusion, and family associated with emotions like joy and trust. But responses are far from uniform: drag culture and brand activism generate polarized reactions, driven by discomfort with nontraditional gender expressions and skepticism about corporate authenticity. Crucially, consumers aren't just reacting to the ad itself. They're evaluating the brand behind it, questioning whether its support reflects genuine values or "rainbow-washing."
The practical takeaways for advertisers are threefold: treat inclusion as a long-term commitment rather than a one-off campaign, recognize that different forms of LGBTQ representation call for different communication strategies, and mine the comment section, which often reveals more than views and engagement metrics ever could. The discussion also digs into the challenge of interpreting sarcasm and irony in online comments, why the authors paired computational analysis with extensive manual validation, and where this research should go next, from cross-platform comparisons to cross-cultural work.
Read the full paper here: https://doi.org/10.1080/00218499.2025.2554437
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