Mapping Topics in 100,000 Real-Life Moral Dilemmas
Keywords:Qualitative and quantitative studies of social media, Text categorization; topic recognition; demographic/gender/age identification, Subjectivity in textual data; sentiment analysis; polarity/opinion identification and extraction, linguistic analyses of social media behavior, Credibility of online content
AbstractMoral dilemmas play an important role in theorizing both about ethical norms and moral psychology. Yet thought experiments borrowed from the philosophical literature often lack the nuances and complexity of real life. We leverage 100,000 threads—the largest collection to date—from Reddit’s r/AmItheAsshole to examine the features of everyday moral dilemmas. Combining topic modeling with evaluation from both expert and crowd-sourced workers, we discover 47 fine-grained, meaningful topics and group them into five meta-categories. We show that most dilemmas combine at least two topics, such as family and money. We also observe that the pattern of topic co-occurrence carries interesting information about the structure of everyday moral concerns: for example, the generation of moral dilemmas from nominally neutral topics, and interaction effects in which final verdicts do not line up with the moral concerns in the original stories in any simple way. Our analysis demonstrates the utility of a fine-grained data-driven approach to online moral dilemmas, and provides a valuable resource for researchers aiming to explore the intersection of practical and theoretical ethics.
How to Cite
Nguyen, T. D., Lyall, G., Tran, A., Shin, M., Carroll, N. G., Klein, C., & Xie, L. (2022). Mapping Topics in 100,000 Real-Life Moral Dilemmas. Proceedings of the International AAAI Conference on Web and Social Media, 16(1), 699-710. Retrieved from https://ojs.aaai.org/index.php/ICWSM/article/view/19327