This study examines how Chinese mothers adjust their affective expressions on social media under the dual influence of algorithmic governance and gendered norms. Based on semi-structured interviews with 21 active yet pre-commercial mothers across Douyin, Xiaohongshu, and WeChat Channels, and using thematic analysis supported by GPT-4 as an anonymized analytical aid, the study identifies four expressive strategies: tonal softening, indirect articulation, imitation of popular styles, and fragmented expressions of restrained emotion. These strategies sustain visibility while aligning with the “good mother” ideal, revealing ongoing affective calibration between platform logics and cultural expectations. The study proposes the concept of “algorithmically attuned affective labor” (AAL) to describe this adaptive emotional work shaped by predictive interaction with recommendation systems. Findings show that digital motherhood in China is both a site for cultural norm reproduction and a nexus where algorithmic governance intersects with unpaid affective labor, highlighting the need for more transparent, inclusive algorithms that support diverse emotional expression.
Li et al. (Mon,) studied this question.