Methods in predictive techniques for mental health status on social media: a critical review
Social media is now being used to model mental well-being, and for understanding health
outcomes. Computer scientists are now using quantitative techniques to predict the …
outcomes. Computer scientists are now using quantitative techniques to predict the …
Suicidal ideation detection: A review of machine learning methods and applications
Suicide is a critical issue in modern society. Early detection and prevention of suicide
attempts should be addressed to save people's life. Current suicidal ideation detection (SID) …
attempts should be addressed to save people's life. Current suicidal ideation detection (SID) …
Using social media for mental health surveillance: a review
Data on social media contain a wealth of user information. Big data research of social media
data may also support standard surveillance approaches and provide decision-makers with …
data may also support standard surveillance approaches and provide decision-makers with …
Detection of suicide ideation in social media forums using deep learning
Suicide ideation expressed in social media has an impact on language usage. Many at-risk
individuals use social forum platforms to discuss their problems or get access to information …
individuals use social forum platforms to discuss their problems or get access to information …
Detecting and analyzing suicidal ideation on social media using deep learning and machine learning models
Individuals who suffer from suicidal ideation frequently express their views and ideas on
social media. Thus, several studies found that people who are contemplating suicide can be …
social media. Thus, several studies found that people who are contemplating suicide can be …
Who is the" human" in human-centered machine learning: The case of predicting mental health from social media
" Human-centered machine learning"(HCML) combines human insights and domain
expertise with data-driven predictions to answer societal questions. This area's inherent …
expertise with data-driven predictions to answer societal questions. This area's inherent …
A taxonomy of ethical tensions in inferring mental health states from social media
Powered by machine learning techniques, social media provides an unobtrusive lens into
individual behaviors, emotions, and psychological states. Recent research has successfully …
individual behaviors, emotions, and psychological states. Recent research has successfully …
Supervised learning for suicidal ideation detection in online user content
Early detection and treatment are regarded as the most effective ways to prevent suicidal
ideation and potential suicide attempts—two critical risk factors resulting in successful …
ideation and potential suicide attempts—two critical risk factors resulting in successful …
Automatic detection of depression symptoms in twitter using multimodal analysis
Depression is the most prevalent mental disorder that can lead to suicide. Due to the
tendency of people to share their thoughts on social platforms, social data contain valuable …
tendency of people to share their thoughts on social platforms, social data contain valuable …
A time-aware transformer based model for suicide ideation detection on social media
Social media's ubiquity fosters a space for users to exhibit suicidal thoughts outside of
traditional clinical settings. Understanding the build-up of such ideation is critical for the …
traditional clinical settings. Understanding the build-up of such ideation is critical for the …