We study how bots contribute to open-source discussions in the Ethereum ecosystem and whether they influence developers' emotional tone. Our dataset covers 36,875 accounts across ten repositories with 105 validated bots (0.28%). Human participation follows a U-shaped pattern, while bots engage in uniform (pull requests) or late-stage (issues) activity. Bots respond faster than humans in pull requests but play slower maintenance roles in issues. Using a model trained on 27 emotion categories, we find bots are more neutral, yet their interventions are followed by reduced neutrality in human comments, with shifts toward gratitude, admiration, and optimism and away from confusion. These findings indicate that even a small number of bots are associated with changes in both timing and emotional dynamics of developer communication.

翻译：本研究探讨了机器人在以太坊生态系统的开源讨论中的贡献方式及其对开发者情感基调的影响。我们的数据集涵盖十个代码库中的36,875个账户，其中包含105个经核实的机器人（占比0.28%）。人类参与呈现U型分布模式，而机器人在拉取请求中表现为均匀参与，在问题讨论中则集中于后期阶段。机器人在拉取请求中的响应速度优于人类，但在问题讨论中承担着节奏较慢的维护性角色。通过基于27种情感类别训练的模型分析，我们发现机器人表现更为中立，但其介入后人类评论的中立性降低，情感倾向朝感激、赞赏和乐观方向转移，同时困惑情绪减少。这些发现表明，即使数量有限的机器人也与开发者交流的时间模式和情感动态变化存在关联。