Online Q&A communities are built around both knowledge sharing and visible interactions among contributors, creating conditions in which contributors may be influenced by the emotional tone of prior answers. Drawing on emotional contagion theory and cognitive reappraisal, this study examines whether and how emotions spread among knowledge contributors, and how such contagion is shaped by cognitive engagement and social status. Using a large-scale dataset from Zhihu, we measure answer sentiment through LIWC-based text analysis, control for topic heterogeneity with topic modeling, and estimate cross-classified hierarchical linear models that account for answers nested within both questions and contributors. We also use an instrumental variable approach to address potential endogeneity. The results show that prior answers’ emotional tone significantly predicts the sentiment of subsequent contributions, indicating emotional contagion in a weak-tie, task-oriented knowledge community. This effect is weakened when contributors engage in more substantive elaboration, suggesting a rationality cooling mechanism, especially for negative sentiment. Further valence-specific analyses reveal an asymmetric role of social status. High-status contributors are less responsive to positive peer sentiment, consistent with an objective image-maintenance motive, but are more responsive to negative peer sentiment, suggesting the strategic use of negativity to signal expertise and critical discernment. This study reframes sentiment in UGC as a dynamic behavioral outcome shaped by peer exposure, cognitive regulation, and status-based self-presentation, offering implications for platform designs that reduce emotional polarization by encouraging cognitive effort.
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