Abstract
Brands are embracing sociopolitical issues in their advertising campaigns, a strategy termed “woke advertising,” to tailor to contemporary social movements. To create social impact, brands upload the woke campaigns on social media platforms, such as YouTube, to arouse discussion. However, the conversation among consumers regarding a woke campaign may move from level-headed debate to emotionally fueled fighting. Thus, research is needed to understand why consumers generate hate/toxic speech in the context of woke advertising. Based on previous research, we adopted machine learning algorithms to classify the comments on two woke campaigns into toxic and nontoxic comments, analyzed the topics of each comment type, examined the engagement performance of each comment type, and tracked the growth of each type of comments over time. Empirical findings shed light on two main sources of cognitive dissonance in the context of woke advertising (i.e., the stance of the woke campaign and others’ comments on the woke campaign) and indicate that both supporters and opposers of a woke campaign may use hate/toxic speech to attack the source of cognitive dissonance. Moreover, given the source of cognitive dissonance, consumers may or may not leverage their persuasion knowledge to cope with a woke campaign.
Disclosure Statement
No potential conflict of interest was reported by the author(s).
Notes
1 The Python script is available here: https://github.com/hridaydutta123/the-youtube-scraper. Please be aware that the script may be outdated, as YouTube frequently updates its platform.