Unraveling Affective Responses and Core Determinants in Health and Trauma-Driven Suicidal Narratives

Suicidal tendencies represent a significant mental health concern, affecting millions worldwide and resulting in a substantial loss of life. Suicidal ideation can arise from various factors, including health complications, social isolation, familial abuse, traumatic events, relationship breakdowns, and financial strain. This study focuses on two key determinants of suicidal ideation: health-related conditions and traumatic life experiences. By employing natural language processing (NLP) techniques and neural network-based emotion recognition models, the study aims to elucidate the distinct characteristics of suicidal posts associated with each factor, with particular emphasis on emotional dynamics. Additionally, we seek to understand how each factor influences suicidal ideation through thematic analysis and a more granular examination of determinants. Emotion analysis reveals that anger is the most dominant emotion, constituting nearly 20% of suicidal posts linked to health issues and traumatic life experiences, alongside various other negative emotions. Health issues identified in suicidal posts encompass a range of both physical and mental health conditions, including depression, anxiety, panic disorders, physical disabilities, and chronic pain. Moreover, various forms of abuse—such as controlling behaviors, family violence, abusive relationships, and bullying—within the context of traumatic life events, are associated with suicidal tendencies. Our findings provide critical insights into the relationships between suicidal ideation, health issues, and traumatic life experiences, which can inform the development of targeted suicide prevention strategies.