Algorithm-shaped norms: how YouTube’s comment ranking algorithm influences consumer reactions to social issue campaigns

Purpose Brands often launch social issue campaigns on platforms like YouTube to stimulate consumer conversation, with varying impacts on the original campaign. Building on the literature on algorithmic popularity bias and social norms, this study aims to explore how algorithm-ranked top comments shape perceived dominant opinions and consumer responses to campaigns promoting inclusive gender identity. Design/methodology/approach In the algorithmic social media environment, user conformity to top comments shapes prevalent opinions about a campaign, subsequently driving further conformity, reinforcing certain opinions and ultimately making them dominant. Using grounded theory, this study identifies four types of conformity through interviews with 23 YouTube users: passive, indirect, direct and active. Findings Each type reflects a different degree of agreement with top comments and a distinct willingness to express opinions. These conformity types play a pivotal role in shaping and reinforcing dominant opinions on gender-themed campaigns. Originality/value This study offers a novel framework that identifies four types of user conformity in response to algorithm-ranked top comments on social issue campaigns: passive, indirect, direct and active.