Mental distress emerged as a significant area of concern. However, previous research predominantly concentrated on the detection and classification of mental issues, with limited attention given to comprehensive investigations of the interrelationships and contextual events associated with these issues. This research delves into the exploration of mental distress derived from user-generated content on the r/AmItheAsshole subreddit. The experimental data contains 1,888,423 words from 5051 English posts. Through the utilization of NLP techniques, including emotion classification, topic modeling, and semantic role labeling, the study revealed a significant prevalence of negative emotions (94 %) such as sadness, anger, and fear in the analyzed content. Furthermore, a combined BERTopic and narrative analysis shed light on the trivial origins of these conflicts. A potentialcorrelation between heightened intimacy and an increased occurrence of disagreements was discerned. As online communities become increasingly instrumental in people’s daily lives, this paper emphasizes their potential in providing invaluable insights to psychologists and sociologists, thereby enabling the formulation of effective strategies and interventions. We recommend educational endeavors to nurture empathy and promote effective communication. Our dataset and codes have been uploaded to GitHub.
Qinghao Guan (Wed,) studied this question.