#InfantFood: Women's Subtle Resistance under the Algorithmic Gaze of Rednote Users

Although Rednote's user demographic is mostly female (70-80%), numerous individuals claim to encounter harassment from male users. In this environment, female users construct a sophisticated coping technique that has not been adequately studied. This study investigates the phenomenon of female users intentional appropriation of the hashtag #InfantFood on Rednote to minimize the visibility of their posts to male users. Based on the theory of algorithmic bias, the study endeavors to solve the central questions: why do female users choose the specific hashtag #InfantFood? How does it achieve dual resistance against traditional gender discipline and algorithmic bias? The current study proposes that female users' appropriation of #InfantFood serves as a subtle form of resistance to subvert the algorithmic bias and gender discipline embedded in #InfantFood, rendering a safe space where women are empowered to have a voice, while the practice also raises concern about gender segregation and the formation of echo chambers, which may exacerbate misunderstandings and conflicts between genders. This paper offers a novel perspective on the interplay between algorithmic bias, gender discrimination, and online harassment and offers insights for a reevaluation of algorithmic design to promote gender equality in digital spaces.