Machine ethics ensures ethical conduct in Artificial Intelligence (AI) models and agents. Examining real-life applications benefit learning practical ethics in many situations, offering valuable data to grasp the complexities of human ethics in diverse contexts. In this paper, we examine social media platforms for understanding real-life ethical scenarios and human moral judgments. We examine posts from a popular Reddit subreddit (i.e., a subcommunity) called r/AmITheAsshole, where authors and commenters share their moral judgments on who is blameworthy. We employ computational techniques to investigate the underlying reasoning influencing moral judgments. We focus on excerpts-which we term moral sparks-from original posts that commenters include to indicate what motivates their judgments. To this end, we examine how (1) events activating social commonsense and (2) linguistic signals affect moral sparks assignment and their subsequent judgments. By examining over 24 672 posts and 175988 comments, we find that event-related negative character traits (e.g., immature and rude) attract attention and stimulate blame, implying a dependent relationship between character traits and moral values. Specially, we focus on causal graph involving events (c-events) that activate social commonsense. We observe that c-events are perceived with varying levels of informativeness, influencing moral spark and judgment assignment in distinct ways. This observation is reinforced by examining linguistic features describing semantically similar c-events. Moreover, language influencing commenters' cognitive processes enhances the probability of an excerpt becoming a moral spark, while factual and concrete descriptions tend to inhibit this effect.

翻译：机器伦理确保人工智能模型与代理的伦理行为。审视现实应用有助于在多种场景中学习实践伦理，为理解不同情境下人类伦理的复杂性提供宝贵数据。本文通过社交媒体平台探究现实伦理场景与人类道德判断。我们分析了热门Reddit子社区（子社群）r/AmITheA-hole中的帖子，其中作者与评论者就谁应受谴责分享道德判断。采用计算方法探究影响道德判断的潜在推理机制，重点关注评论者用于说明动机的原文片段（称为"道德火花"）。为此，研究：（1）激活社会常识的事件与（2）语言信号如何影响道德火花分配及其后续判断。通过分析24672篇帖子与175988条评论，发现与事件相关的负面性格特征（如不成熟、粗鲁）会吸引注意并引发谴责，表明性格特征与道德价值观之间存在依存关系。特别聚焦于激活社会常识的因果事件（c-events），观察到这些事件被感知的信息量存在差异，并以不同方式影响道德火花与判断分配。这一发现通过描述语义相似c-events的语言特征分析得到强化。此外，影响评论者认知过程的语言会提升片段成为道德火花概率，而事实性、具体性描述则倾向于抑制该效应。