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The purpose of this paper is to identify the degree of depression based on people's behavioral patterns and discussion content on the Internet.<\/jats:p><\/jats:sec><jats:sec><jats:title content-type=\"abstract-subheading\">Design\/methodology\/approach<\/jats:title><jats:p>Based on the previous studies on depression, the severity of depression is divided into four categories: no significant depressive symptoms, mild MDD, moderate MDD and severe MDD, and defined each of them. Next, in order to automatically identify the severity, the authors proposed social media digital cues to identify the severity of depression, which include textual lexical features, depressive language features and social behavioral features. Finally, the authors evaluate a system that is developed based on social media digital cues in the experiment using social media data.<\/jats:p><\/jats:sec><jats:sec><jats:title content-type=\"abstract-subheading\">Findings<\/jats:title><jats:p>The social media digital cues including textual lexical features, depressive language features and social behavioral features (F1, F2 and F3) is the relatively best one to classify four different levels of depression.<\/jats:p><\/jats:sec><jats:sec><jats:title content-type=\"abstract-subheading\">Originality\/value<\/jats:title><jats:p>This paper innovatively proposes a social media data-based framework (SMDF) to identify and predict different degrees of depression through social media digital cues and evaluates the accuracy of the detection through social media data, providing useful attempts for the identification and intervention of depression.<\/jats:p><\/jats:sec>","DOI":"10.1108\/imds-12-2022-0754","type":"journal-article","created":{"date-parts":[[2023,9,27]],"date-time":"2023-09-27T05:48:49Z","timestamp":1695793729000},"page":"3038-3052","source":"Crossref","is-referenced-by-count":5,"title":["Detecting depression and its\u00a0severity based on social media\u00a0digital cues"],"prefix":"10.1108","volume":"123","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-4515-6290","authenticated-orcid":false,"given":"Shasha","family":"Deng","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xuan","family":"Cheng","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8007-3028","authenticated-orcid":false,"given":"Rong","family":"Hu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"140","published-online":{"date-parts":[[2023,9,29]]},"reference":[{"key":"key2023120405532407200_ref001","doi-asserted-by":"publisher","first-page":"581","DOI":"10.1109\/ICSC.2008.61","article-title":"Topic detection and extraction in chat","year":"2008"},{"issue":"2","key":"key2023120405532407200_ref002","doi-asserted-by":"publisher","first-page":"427","DOI":"10.25300\/MISQ\/2018\/13239","article-title":"Text analytics to support sense-making in social media: a language-action perspective","volume":"42","year":"2018","journal-title":"MIS Quarterly"},{"issue":"3","key":"key2023120405532407200_ref003","doi-asserted-by":"publisher","first-page":"231","DOI":"10.1111\/1467-9450.00192","article-title":"Dimensions of fatigue in different working populations","volume":"41","year":"2000","journal-title":"Scandinavian Journal of Psychology"},{"key":"key2023120405532407200_ref004","doi-asserted-by":"publisher","first-page":"351","DOI":"10.1016\/j.chb.2015.08.023","article-title":"A content analysis of depression-related tweets","volume":"54","year":"2016","journal-title":"Computers in Human Behavior"},{"key":"key2023120405532407200_ref005","doi-asserted-by":"publisher","first-page":"10","DOI":"10.1016\/j.specom.2015.03.004","article-title":"A review of depression and suicide risk assessment using speech analysis","volume":"71","year":"2015","journal-title":"Speech Communication"},{"key":"key2023120405532407200_ref006","article-title":"Predicting depression via social media","year":"2013"},{"issue":"16","key":"key2023120405532407200_ref007","doi-asserted-by":"publisher","first-page":"6351","DOI":"10.1016\/j.eswa.2013.05.050","article-title":"Emotion detection in suicide notes","volume":"40","year":"2013","journal-title":"Expert Systems with Applications"},{"issue":"4","key":"key2023120405532407200_ref008","doi-asserted-by":"publisher","first-page":"713","DOI":"10.1007\/s10608-012-9517-9","article-title":"Why are depressive individuals indecisive? 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