Unlocking the narrative: Using text mining to reveal the hidden factors behind suicide related traffic crashes

Suicide is the deliberate act of ending a person’s own life due to multifarious reasons. In the U.S., suicide is the 10th major cause of death. Nearly 45,000 people died by suicide in 2016 across the nation. It is anticipated that not all traffic crashes can be considered as accidents. Traffic crash related injuries are […]

Toward automatic risk assessment to support suicide prevention

Background: Suicide has been considered an important public health issue for years and is one of the main causes of death worldwide. Despite prevention strategies being applied, the rate of suicide has not changed substantially over the past decades. Suicide risk has proven extremely difficult to assess for medical specialists, and traditional methodologies deployed have been […]

Applying text mining methods to suicide research

Objective To introduce the research methods of computerized text mining and its possible applications in suicide research and to demonstrate the procedures of applying a specific text mining area, document classification, to a suicide-related study. Method A systematic search of academic papers that applied text mining methods to suicide research was conducted. Relevant papers were […]

The use of text-based responses to improve our understanding and prediction of suicide risk

Objective Text-based responses may provide significant contributions to suicide risk prediction, yet research including text data is limited. This may be due to a lack of exposure and familiarity with statistical analyses for this data structure. Method The current study provides an overview of data processing and statistical algorithms for text data, guided by an […]

A critical review of text mining applications for suicide research

Purpose of Review Applying text mining to suicide research holds a great deal of promise. In this manuscript, literature from 2019 to 2021 is critically reviewed for text mining projects that use electronic health records, social media data, and death records. Recent Findings Text mining has helped identify risk factors for suicide in general and […]

Cognitive networks identify dimensions of distress in suicide notes: Anxiety, emotional profiles, and the “words not said”

Suicide remains a serious public-health concern that is difficult to accurately predict in real-world settings. To identify potential predictors of suicide, we examined the emotional content of suicide notes using methods from cognitive network science. Specifically, we compared the co-occurrence networks of suicide notes with those constructed out of emotion words written by individuals scoring […]

Suicide and the agent-host-environment triad: Leveraging surveillance sources to inform prevention

Suicide in the US has increased in the last decade, across virtually every age and demographic group. Parallel increases have occurred in non-fatal self-harm as well. Research on suicide across the world has consistently demonstrated that suicide shares many properties with a communicable disease, including person-to-person transmission and point-source outbreaks. This essay illustrates the communicable […]

Suicide-related Twitter content in response to a national mental health awareness campaign and the association between the campaign and suicide rates in Ontario

Objective: Mental health awareness (MHA) campaigns have been shown to be successful in improving mental health literacy, decreasing stigma, and generating public discussion. However, there is a dearth of evidence regarding the effects of these campaigns on behavioral outcomes such as suicides. Therefore, the objective of this article is to characterize the association between the event […]

Towards ordinal suicide ideation detection on social media

The rising ubiquity of social media presents a platform for individuals to express suicide ideation, instead of traditional, formal clinical settings. While neural methods for assessing suicide risk on social media have shown promise, a crippling limitation of existing solutions is that they ignore the inherent ordinal nature across finegrain levels of suicide risk. To […]

Public response to suicide news reports as reflected in computerized text analysis of online reader comments

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 […]

Natural language processing of social media as screening for suicide risk

Suicide is among the 10 most common causes of death, as assessed by the World Health Organization. For every death by suicide, an estimated 138 people’s lives are meaningfully affected, and almost any other statistic around suicide deaths is equally alarming. The pervasiveness of social media—and the near-ubiquity of mobile devices used to access social […]

Automatic extraction of informal topics from online suicidal ideation

Background Suicide is an alarming public health problem accounting for a considerable number of deaths each year worldwide. Many more individuals contemplate suicide. Understanding the attributes, characteristics, and exposures correlated with suicide remains an urgent and significant problem. As social networking sites have become more common, users have adopted these sites to talk about intensely […]