Resource Tag: LINGUISTIC ANALYSIS (LINGUISTICS)

Suicide, as an increasingly prominent social problem, has attracted widespread social attention in the mental health field. Traditional suicide clinical assessment and risk questionnaires lack timeliness and proactivity, and high-risk groups often conceal their intentions, which is not conducive to early suicide prevention. In this study, we used machine-learning algorithms to extract text features from […]

Objective With early identification and intervention, many suicidal deaths are preventable. Tools that include machine learning methods have been able to identify suicidal language. This paper examines the persistence of this suicidal language up to 30 days after discharge from care. Method In a multi-center study, 253 subjects were enrolled into either suicidal or control cohorts. […]

Suicide represents a public health issue that requires new preventive strategies. Therefore, this study analyzes differences in language use between a themed posts group (suicide and depression) and a random posts group (non-specific topics) from different social media platforms. In addition, the similarity of the texts of themed posts group with the set of phrases […]

Previous research has documented the rise in rates of suicidal behaviors following media reports of celebrity suicide. Whereas most research has focused on documenting and analyzing suicide rates, little is known about more subtle psychological effects of celebrity suicide on the public, such as despair and feelings of abandonment. The Internet has revolutionized the responses […]

This study aims to describe the psychological process, language features and the cause’s factors of student’s suicide notes. This study explores the power of linguistic variables to uncover the hidden meaning of suicide notes. This analysis uses computerized text analysis namely Linguistic Inquiry and Word Count (LIWC) program and forensic semantic analysis. The primary data […]

Background: Suicide is a leading cause of death worldwide. Identifying those at risk and delivering timely interventions is challenging. Social media site Twitter is used to express suicidality. Automated linguistic analysis of suicide-related posts may help to differentiate those who require support or intervention from those who do not. Aims: This study aims to characterize the linguistic profiles […]