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The authors searched Twitter for tweets indicative of 12 suicide risk factors. This paper divided Twitter users into two groups: \u201chigh risk\u201d and \u201cat risk\u201d based on two of the risk factors (\u201cself-harm\u201d and \u201cprior suicide attempts\u201d) and examined language patterns by computing co-occurrences of terms in tweets which helped identify relationships between suicide risk factors in both groups.<\/jats:p>","DOI":"10.4018\/ijkdb.2018070101","type":"journal-article","created":{"date-parts":[[2018,9,28]],"date-time":"2018-09-28T17:59:33Z","timestamp":1538157573000},"page":"1-17","source":"Crossref","is-referenced-by-count":4,"title":["Suicide Risk on Twitter"],"prefix":"10.4018","volume":"8","author":[{"given":"Samah Jamal","family":"Fodeh","sequence":"first","affiliation":[{"name":"Yale University, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Edwin D.","family":"Boudreaux","sequence":"additional","affiliation":[{"name":"University of Massachusetts Medical School, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Rixin","family":"Wang","sequence":"additional","affiliation":[{"name":"Yale University, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Dennis","family":"Silva","sequence":"additional","affiliation":[{"name":"Worcester Polytechnic Institute, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Robert","family":"Bossarte","sequence":"additional","affiliation":[{"name":"Department of Veteran Affairs, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Joseph Lucien","family":"Goulet","sequence":"additional","affiliation":[{"name":"Department of Veteran Affairs, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Cynthia","family":"Brandt","sequence":"additional","affiliation":[{"name":"Yale University, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Hamada Hamid","family":"Altalib","sequence":"additional","affiliation":[{"name":"Yale University, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"2432","reference":[{"key":"IJKDB.2018070101-0","doi-asserted-by":"crossref","first-page":"250","DOI":"10.1007\/978-3-319-07983-7_36","article-title":"Mining twitter for suicide prevention","author":"A.Abboute","year":"2014","journal-title":"Natural Language Processing and Information Systems"},{"key":"IJKDB.2018070101-1","year":"2016"},{"key":"IJKDB.2018070101-2","doi-asserted-by":"publisher","DOI":"10.1016\/j.aaen.2007.04.005"},{"key":"IJKDB.2018070101-3","doi-asserted-by":"publisher","DOI":"10.1176\/ajp.145.8.971"},{"key":"IJKDB.2018070101-4","doi-asserted-by":"publisher","DOI":"10.1176\/appi.ajp.162.2.297"},{"key":"IJKDB.2018070101-5","first-page":"785","article-title":"Suicide detection system based on Twitter.","author":"V. 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