Emotional Contagion in Code: How GitHub Emoji Reactions Shape Developer Collaboration
This study investigates whether emoji reactions on GitHub drive emotional contagion and influence developer collaboration outcomes. Method: Analyzing 106,743 emoji reactions across 2,098 issues/pull requests, we employed sentiment polarity classification, social network cascade analysis, effect-size estimation (Cohen’s *d*), and correlation analysis. Contribution/Results: We identify significant positive emotional contagion in technical discussions (*r* = 0.679, *d* = 2.393), with a positive-to-negative emotional cascade ratio of 23:1; 57.4% of discussions exhibit dominant positive sentiment. We propose and empirically validate five distinct emoji-driven emotional propagation patterns, demonstrating that initial affective feedback strongly steers discussion trajectories. Findings establish emoji not merely as expressive tokens but as critical affective signaling mechanisms shaping collaborative dynamics. This work provides empirical grounding and methodological insights for human-AI collaboration and affective computing in open-source communities.