Exploring and Learning Suicidal Ideation Connotations on Social Media with Deep Learning

no code implementations • WS 2018 • Ramit Sawhney, Manch, Prachi a, Puneet Mathur, Rajiv Shah, Raj Singh

The increasing suicide rates amongst youth and its high correlation with suicidal ideation expression on social media warrants a deeper investigation into models for the detection of suicidal intent in text such as tweets to enable prevention.

General Classification Sentence +2

A Computational Approach to Feature Extraction for Identification of Suicidal Ideation in Tweets

no code implementations • ACL 2018 • Ramit Sawhney, Manch, Prachi a, Raj Singh, Swati Aggarwal

Technological advancements in the World Wide Web and social networks in particular coupled with an increase in social media usage has led to a positive correlation between the exhibition of Suicidal ideation on websites such as Twitter and cases of suicide.

TWINE: A real-time system for TWeet analysis via INformation Extraction

no code implementations • EACL 2017 • Debora Nozza, Fausto Ristagno, Matteo Palmonari, Elisabetta Fersini, Manch, Pikakshi a, Enza Messina

In this paper we present TWINE, a real-time system for the big data analysis and exploration of information extracted from Twitter streams.

named-entity-recognition Named Entity Recognition +1