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This paper presents an approach to understand suicidal ideation through online user\u2010generated content with the goal of early detection via supervised learning. Analysing users\u2019 language preferences and topic descriptions reveals rich knowledge that can be used as an early warning system for detecting suicidal tendencies. Suicidal individuals express strong negative feelings, anxiety, and hopelessness. Suicidal thoughts may involve family and friends. And topics they discuss cover both personal and social issues. To detect suicidal ideation, we extract several informative sets of features, including statistical, syntactic, linguistic, word embedding, and topic features, and we compare six classifiers, including four traditional supervised classifiers and two neural network models. An experimental study demonstrates the feasibility and practicability of the approach and provides benchmarks for the suicidal ideation detection on the active online platforms: Reddit SuicideWatch and Twitter.<\/jats:p>","DOI":"10.1155\/2018\/6157249","type":"journal-article","created":{"date-parts":[[2018,9,9]],"date-time":"2018-09-09T23:31:26Z","timestamp":1536535886000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":149,"title":["Supervised Learning for Suicidal Ideation Detection in Online User Content"],"prefix":"10.1155","volume":"2018","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-3281-8002","authenticated-orcid":false,"given":"Shaoxiong","family":"Ji","sequence":"first","affiliation":[]},{"given":"Celina Ping","family":"Yu","sequence":"additional","affiliation":[]},{"given":"Sai-fu","family":"Fung","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0794-527X","authenticated-orcid":false,"given":"Shirui","family":"Pan","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3740-9515","authenticated-orcid":false,"given":"Guodong","family":"Long","sequence":"additional","affiliation":[]}],"member":"311","published-online":{"date-parts":[[2018,9,9]]},"reference":[{"key":"e_1_2_9_1_2","unstructured":"Suicide rates Global Health Observatory (GHO) data 2015 http:\/\/www.who.int\/gho\/mental_health\/suicide_rates\/en\/."},{"key":"e_1_2_9_2_2","doi-asserted-by":"publisher","DOI":"10.1109\/TAFFC.2016.2518665"},{"key":"e_1_2_9_3_2","volume-title":"Foundations of Machine Learning","author":"Mohri M.","year":"2012"},{"key":"e_1_2_9_4_2","doi-asserted-by":"publisher","DOI":"10.1007\/BF00994018"},{"key":"e_1_2_9_5_2","doi-asserted-by":"publisher","DOI":"10.1023\/A:1010933404324"},{"key":"e_1_2_9_6_2","doi-asserted-by":"publisher","DOI":"10.1214\/aos\/1013203451"},{"key":"e_1_2_9_7_2","doi-asserted-by":"crossref","unstructured":"ChenT.andGuestrinC. 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