相关论文: A Quantitative and Qualitative Analysis of Suicide…

This review underscores the critical need for effective strategies to identify and support individuals with suicidal ideation, exploiting technological innovations in ML and DL to further suicide prevention efforts. The study details the…

Mental health is a critical issue in modern society, and mental disorders could sometimes turn to suicidal ideation without effective treatment. Early detection of mental disorders and suicidal ideation from social content provides a…

Suicide is a critical global health problem involving more than 700,000 deaths yearly, particularly among young adults. Many people express their suicidal thoughts on social media platforms such as Reddit. This paper evaluates the…

With social media communities increasingly becoming places where suicidal individuals post and congregate, natural language processing presents an exciting avenue for the development of automated suicide risk assessment systems. However,…

The collection and examination of social media has become a useful mechanism for studying the mental activity and behavior tendencies of users. Through the analysis of collected Twitter data, models were developed for classifying…

In the social media, users frequently express personal emotions, a subset of which may indicate potential suicidal tendencies. The implicit and varied forms of expression in internet language complicate accurate and rapid identification of…

Suicide remains one of the main preventable causes of death among active service members and veterans. Early detection and prediction are crucial in suicide prevention. Machine learning techniques have yielded promising results in this area…

A large number of individuals are suffering from suicidal ideation in the world. There are a number of causes behind why an individual might suffer from suicidal ideation. As the most popular platform for self-expression, emotion release,…

Preventing Veteran suicide is a national priority. The US Department of Veterans Affairs (VA) collects, analyzes, and publishes data to inform suicide prevention strategies. Current approaches for detecting suicidal ideation mostly rely on…

Suicide is a critical global health issue that requires urgent attention. Even though prior work has revealed valuable insights into detecting current suicide risk on social media, little attention has been paid to developing models that…

Textual emotional intelligence is playing a ubiquitously important role in leveraging human emotions on social media platforms. Social media platforms are privileged with emotional content and are leveraged for various purposes like opinion…

The detection of suicide risk in social media is a critical task with potential life-saving implications. This paper presents a study on leveraging state-of-the-art natural language processing solutions for identifying suicide risk in…

Despite detection of suicidal ideation on social media has made great progress in recent years, people's implicitly and anti-real contrarily expressed posts still remain as an obstacle, constraining the detectors to acquire higher…

The COVID-19 pandemic has escalated mental health crises worldwide, with social isolation and economic instability contributing to a rise in suicidal behavior. Suicide can result from social factors such as shame, abuse, abandonment, and…

Cyberbullying is a disturbing online misbehaviour with troubling consequences. It appears in different forms, and in most of the social networks, it is in textual format. Automatic detection of such incidents requires intelligent systems.…

Though suicide is a major public health problem in the US, machine learning methods are not commonly used to predict an individual's risk of attempting/committing suicide. In the present work, starting with an anonymized collection of…

Suicide is among the leading causes of death in China. However, technical approaches toward preventing suicide are challenging and remaining under development. Recently, several actual suicidal cases were preceded by users who posted…

The promising research on Artificial Intelligence usages in suicide prevention has principal gaps, including black box methodologies, inadequate outcome measures, and scarce research on non-verbal inputs, such as social media images…

Suicide is a critical global public health issue, with millions experiencing suicidal ideation (SI) each year. Online spaces enable individuals to express SI and seek peer support. While prior research has revealed the potential of…

Online social media platforms have recently become integral to our society and daily routines. Every day, users worldwide spend a couple of hours on such platforms, expressing their sentiments and emotional state and contacting each other.…