With the rapid development of social media, the new challenge comes out: how to cope with online public opinion crisis in enterprise. Our study solves the problem from the perspective of how to repair public trust effectively. To be specific, we construct a unique data set about 5 quality defect cases including 13 response announcements and 46,896 online comments. Combining text mining with empirical testing, we measure the effectiveness of different trust repair strategies in different crisis stages, and explore the effect mechanism and optimal combination of trust repair strategy. Our results show that the affective repair strategy is most effective in the acute stage, the informational repair strategy is most effective in the chronic stage, and the functional repair strategy is most effective in the termination stage. Our work contributes important insights to the online public opinion crisis and trust repair literature, and provides management implications for enterprises to repair public trust effectively in online public opinion crises.

随着社交媒体的快速发展，新的挑战出现了：企业如何应对网络舆情危机。我们的研究从如何有效修复公众信任的角度来解决这个问题。具体而言，我们构建了一个关于 5 个质量缺陷案例的独特数据集，包括 13 个响应公告和 46,896 条在线评论。将文本挖掘与实证检验相结合，衡量不同信任修复策略在不同危机阶段的有效性，探索信任修复策略的效果机制和最优组合。我们的结果表明，情感修复策略在急性期最有效，信息修复策略在慢性期最有效，功能性修复策略在终止期最有效。