Who gets blamed? Negativity bias in social media diffusion on Weibo
DOI:
https://doi.org/10.47989/ir31iConf64147Keywords:
Negativity bias, Social media diffusion, Weibo, Marriage and fertility debatesAbstract
Introduction. This study examines negativity bias in social media diffusion by analysing Weibo discussions on women’s marriage and fertility, focusing on how opinion valence shapes diffusion dynamics.
Method. We collected Weibo posts from January to March 2023, yielding 6,405 original posts and 97,090 diffusion chains after pre-processing. A large language model was used to code opinion polarity of original posts and first-level comments, and regional participant composition was measured to capture contextual heterogeneity.
Analysis. Diffusion depth was operationalised as chain length. Multilevel linear mixed-effects models were employed to estimate the effects of original opinion valence, with first-level comment polarity and regional dominance specified as moderators.
Results. Negative posts triggered deeper, longer diffusion while positive posts curtailed discussion spread. The stance of the first comment played a critical moderating role, that positive originals achieved wider diffusion when initial responses were negative. Regional context further moderated these effects, with eastern-user-dominated chains showing weaker amplification of negativity but stronger diffusion of positive content.
Conclusion. Negativity bias strongly shapes social media diffusion, but its effects are conditional on early audience responses and regional participant composition.
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