{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,28]],"date-time":"2026-08-28T08:36:45Z","timestamp":1787906205199,"version":"build-2784847793"},"reference-count":53,"publisher":"MDPI AG","issue":"6","license":[{"start":{"date-parts":[[2019,3,16]],"date-time":"2019-03-16T00:00:00Z","timestamp":1552694400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["61701104"],"award-info":[{"award-number":["61701104"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IJERPH"],"abstract":"<jats:p>The Institute for Health Metrics and Evaluation (IHME) has stated that over 1.1 billion people suffered from mental disorders globally in 2016, and the burden of mental disorders has continued to grow with impacts on social development. Despite the implementation of strategies for promotion and prevention in mental health WHO\u2019s Comprehensive Mental Health Action Plan 2013\u20132020, the difficulty of diagnosis of mental disorders makes the objective \u201cTo provide comprehensive, integrated, and responsive mental health and social care services in community-based settings\u201d hard to carry out. This paper presents a mental-disorder-aided diagnosis model (MDAD) to quantify the multipolarity sentiment affect intensity of users\u2019 short texts in social networks in order to analyze the 11-dimensional sentiment distribution. We searched the five mental disorder topics and collected data based on Twitter hashtag. Through sentiment distribution similarity calculations and Stochastic Gradient Descent (SGD), people with a high probability of suffering from mental disorder can be detected in real time. In particular, mental health warnings can be made in time for users with an obvious emotional tendency in their tweets. In the experiments, we make a comprehensive evaluation of MDAD by five common adult mental disorders: depressive disorder, anxiety disorder, obsessive-compulsive disorder (OCD), bipolar disorder, and panic disorder. Our proposed model can effectively diagnose common mental disorders by sentiment multipolarity analysis, providing strong support for the prevention and diagnosis of mental disorders.<\/jats:p>","DOI":"10.3390\/ijerph16060953","type":"journal-article","created":{"date-parts":[[2019,3,18]],"date-time":"2019-03-18T12:18:53Z","timestamp":1552911533000},"page":"953","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":33,"title":["Psychological Disorder Identifying Method Based on Emotion Perception over Social Networks"],"prefix":"10.3390","volume":"16","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-3258-0244","authenticated-orcid":false,"given":"Tie Hua","family":"Zhou","sequence":"first","affiliation":[{"name":"Department of Computer Science and Technology, School of Computer Science, Northeast Electric Power University, Jilin 132000, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Gong Liang","family":"Hu","sequence":"additional","affiliation":[{"name":"Department of Computer Science and Technology, School of Computer Science, Northeast Electric Power University, Jilin 132000, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8956-0511","authenticated-orcid":false,"given":"Ling","family":"Wang","sequence":"additional","affiliation":[{"name":"Department of Computer Science and Technology, School of Computer Science, Northeast Electric Power University, Jilin 132000, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2019,3,16]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"18","DOI":"10.1016\/j.puhe.2006.06.018","article-title":"Prevalence, pattern and determinants of mental disorders in rural Bangladesh","volume":"121","author":"Hosain","year":"2007","journal-title":"Public Health"},{"key":"ref_2","doi-asserted-by":"crossref","unstructured":"Ferrari, A.J., Norman, R.E., and Freedman, G. (2014). The burden attributable to mental and substance use disorders as risk factors for suicide: Findings from the Global Burden of Disease Study 2010. PLoS ONE, 9.","DOI":"10.1371\/journal.pone.0091936"},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"1459","DOI":"10.1016\/S0140-6736(16)31012-1","article-title":"Global, regional, and national life expectancy, all-cause mortality, and cause-specific mortality for 249 causes of death, 1980\u20132015: A systematic analysis for the Global Burden of Disease Study 2015","volume":"388","author":"Wang","year":"2016","journal-title":"Lancet"},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"1438","DOI":"10.1016\/S0140-6736(11)60393-0","article-title":"Priority actions for the non-communicable disease crisis","volume":"377","author":"Beaglehole","year":"2011","journal-title":"Lancet"},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"107","DOI":"10.1002\/wps.20141","article-title":"WHO\u2019s Mental Health Action Plan 2013\u20132020: What can psychiatrists do to facilitate its implementation?","volume":"13","author":"Saxena","year":"2014","journal-title":"World Psychiatry"},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"g5189","DOI":"10.1136\/bmj.g5189","article-title":"Including mental health among the new sustainable development goals","volume":"349","author":"Thornicroft","year":"2014","journal-title":"BMJ"},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"30","DOI":"10.1136\/eb-2017-102750","article-title":"WHO Mental Health Gap Action Programme (mhGAP) Intervention Guide: A systematic review of evidence from low and middle-income countries","volume":"21","author":"Keynejad","year":"2017","journal-title":"Evid. Based Ment. Health"},{"key":"ref_8","doi-asserted-by":"crossref","unstructured":"Ho, R.C., Zhang, M.W., and Tsang, T.Y. (2014). The association between internet addiction and psychiatric co-morbidity: A meta-analysis. BMC Psychiatry, 14.","DOI":"10.1186\/1471-244X-14-183"},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"794","DOI":"10.1093\/jpepsy\/jst022","article-title":"Psychometric properties of the internet addiction test in Chinese adolescents","volume":"38","author":"Lai","year":"2013","journal-title":"J. Pediatric Psychol."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1016\/j.eurpsy.2010.04.011","article-title":"The association between Internet addiction and psychiatric disorder: A review of the literature","volume":"27","author":"Ko","year":"2012","journal-title":"Eur. Psychiatry"},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"95","DOI":"10.1097\/NMD.0000000000000428","article-title":"The role of generalized explicit and implicit guilt and shame in interpersonal traumatization and posttraumatic stress disorder","volume":"204","author":"Bockers","year":"2016","journal-title":"J. Nerv. Ment. Dis."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"359","DOI":"10.1097\/YCO.0b013e32816ebc8c","article-title":"Age of onset of mental disorders: A review of recent literature","volume":"20","author":"Kessler","year":"2007","journal-title":"Curr. Opin. Psychiatry"},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"406","DOI":"10.1002\/cncr.30980","article-title":"Course and predictors of post-traumatic stress disorder in a cohort of psychologically distressed patients with cancer: A 4-year follow-up study","volume":"124","author":"Chan","year":"2018","journal-title":"Cancer"},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"2457","DOI":"10.1002\/cncr.31365","article-title":"Reply to Course and predictors of posttraumatic stress disorder in a cohort of psychologically distressed patients with cancer: A 4-year follow-up study\u2014Methodological and statistical issues","volume":"124","author":"Chan","year":"2018","journal-title":"Cancer"},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"28","DOI":"10.1038\/nrneurol.2015.229","article-title":"Clinical assessment of social cognitive function in neurological disorders","volume":"12","author":"Henry","year":"2015","journal-title":"Nat. Rev. Neurol."},{"key":"ref_16","doi-asserted-by":"crossref","unstructured":"Wang, X., Zhang, C., and Ji, Y. (2013, January 14\u201317). A depression detection model based on sentiment analysis in micro-blog social network. Proceedings of the Pacific-Asia Conference on Knowledge Discovery and Data Mining, Berlin, Germany.","DOI":"10.1007\/978-3-642-40319-4_18"},{"key":"ref_17","doi-asserted-by":"crossref","unstructured":"Coppersmith, G., Dredze, M., and Harman, C. (2014, January 27). Quantifying mental health signals in Twitter. Proceedings of the Workshop on Computational Linguistics and Clinical Psychology: From Linguistic Signal to Clinical Reality, Baltimore, MD, USA.","DOI":"10.3115\/v1\/W14-3207"},{"key":"ref_18","doi-asserted-by":"crossref","unstructured":"Ma, G., Wang, C., and Jia, Y. (2018). Electrocardiographic and Electrooculographic Responses to External Emotions and Their Transitions in Bipolar I and II Disorders. Int. J. Environ. Res. Public Health, 15.","DOI":"10.3390\/ijerph15050884"},{"key":"ref_19","doi-asserted-by":"crossref","unstructured":"American Psychiatric Association (2013). Diagnostic and Statistical Manual of Mental Disorders (DSM-5\u00ae), American Psychiatric Pub.","DOI":"10.1176\/appi.books.9780890425596"},{"key":"ref_20","doi-asserted-by":"crossref","unstructured":"Nielsen, E., Sayal, K., and Townsend, E. (2017). Functional coping dynamics and experiential avoidance in a community sample with no self-injury vs. non-suicidal self-injury only vs. those with both non-suicidal self-injury and suicidal behaviour. Int. J. Environ. Res. Public Health, 14.","DOI":"10.3390\/ijerph14060575"},{"key":"ref_21","doi-asserted-by":"crossref","unstructured":"Keyes, C.L. (2003). Complete mental health: An agenda for the 21st century. Flourishing: Positive Psychology and the Life Well-Lived, American Psychological Association.","DOI":"10.1037\/10594-013"},{"key":"ref_22","doi-asserted-by":"crossref","unstructured":"Saura, J.R., Palos-Sanchez, P., and Rios Martin, M.A. (2018). Attitudes Expressed in Online Comments about Environmental Factors in the Tourism Sector: An Exploratory Study. Int. J. Environ. Res. Public Health, 15.","DOI":"10.3390\/ijerph15030553"},{"key":"ref_23","doi-asserted-by":"crossref","unstructured":"Ekenga, C.C., McElwain, C.A., and Sprague, N. (2018). Examining Public Perceptions about Lead in School Drinking Water: A Mixed-Methods Analysis of Twitter Response to an Environmental Health Hazard. Int. J. Environ. Res. Public Health, 15.","DOI":"10.3390\/ijerph15010162"},{"key":"ref_24","doi-asserted-by":"crossref","unstructured":"Wang, L., Hu, G., and Zhou, T. (2018). Semantic Analysis of Learners\u2019 Emotional Tendencies on Online MOOC Education. Sustainability, 10.","DOI":"10.3390\/su10061921"},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1561\/1500000011","article-title":"Opinion mining and sentiment analysis","volume":"2","author":"Pang","year":"2008","journal-title":"Found. Trends Inf. Retr."},{"key":"ref_26","doi-asserted-by":"crossref","unstructured":"Buscaldi, D., and Hernandez-Farias, I. (2015, January 18\u201322). Sentiment analysis on microblogs for natural disasters management: A study on the 2014 genoa floodings. Proceedings of the 24th International Conference on World Wide Web, Florence, Italy.","DOI":"10.1145\/2740908.2741727"},{"key":"ref_27","doi-asserted-by":"crossref","unstructured":"Palomino, M., Taylor, T., and G\u00f6ker, A. (2016). The online dissemination of nature\u2013health concepts: Lessons from sentiment analysis of social media relating to \u201cnature-deficit disorder\u201d. Int. J. Environ. Res. Public Health, 13.","DOI":"10.3390\/ijerph13010142"},{"key":"ref_28","first-page":"1","article-title":"Sentiment analysis and opinion mining","volume":"5","author":"Liu","year":"2012","journal-title":"Synth. Lect. Hum. Lang. Technol."},{"key":"ref_29","doi-asserted-by":"crossref","unstructured":"Coppersmith, G., Dredze, M., and Harman, C. (2015, January 5). From ADHD to SAD: Analyzing the language of mental health on Twitter through self-reported diagnoses. Proceedings of the 2nd Workshop on Computational Linguistics and Clinical Psychology: From Linguistic Signal to Clinical Reality, Denver, CO, USA.","DOI":"10.3115\/v1\/W15-1201"},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"e228","DOI":"10.2196\/jmir.7215","article-title":"Researching mental health disorders in the era of social media: Systematic review","volume":"19","author":"Wongkoblap","year":"2017","journal-title":"J. Med. Internet Res."},{"key":"ref_31","doi-asserted-by":"crossref","unstructured":"Tsugawa, S., Kikuchi, Y., Kishino, F., Nakajima, K., Itoh, Y., and Ohsaki, H. (2015, January 18\u201323). Recognizing depression from twitter activity. Proceedings of the 33rd Annual ACM Conference on Human Factors in Computing Systems, Seoul, Korea.","DOI":"10.1145\/2702123.2702280"},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"301","DOI":"10.1111\/coin.12024","article-title":"Using hashtags to capture fine emotion categories from tweets","volume":"31","author":"Mohammad","year":"2015","journal-title":"Comput. Intell."},{"key":"ref_33","unstructured":"Mohammad, S.M. (2012, January 7\u20138). Emotional tweets. Proceedings of the First Joint Conference on Lexical and Computational Semantics, Montr\u00e9al, QC, Canada."},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"3","DOI":"10.1016\/B978-0-12-558701-3.50007-7","article-title":"A general psychoevolutionary theory of emotion","volume":"Volume 1","author":"Pluchick","year":"1980","journal-title":"Theories of Emotion"},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"385","DOI":"10.1177\/014662167700100306","article-title":"The CES-D scale: A self-report depression scale for research in the general population","volume":"1","author":"Radloff","year":"1977","journal-title":"Appl. Psychol. Meas."},{"key":"ref_36","doi-asserted-by":"crossref","first-page":"601","DOI":"10.1093\/occmed\/kqv054","article-title":"Hamilton Rating Scale for Anxiety (HAM-A)","volume":"65","author":"Thompson","year":"2015","journal-title":"Occup. Med."},{"key":"ref_37","doi-asserted-by":"crossref","first-page":"1006","DOI":"10.1001\/archpsyc.1989.01810110048007","article-title":"The Yale-Brown Obsessive Compulsive Scale","volume":"46","author":"Goodman","year":"1989","journal-title":"Dev. Use Reliab. Arch. Gen. Psychiatry"},{"key":"ref_38","doi-asserted-by":"crossref","first-page":"73","DOI":"10.1097\/00004850-199506000-00003","article-title":"Assessing the efficacy of treatments for panic disorder and agoraphobia: II. The Panic and Agoraphobia Scale","volume":"10","author":"Bandelow","year":"1995","journal-title":"Int. Clin. Psychopharmacol."},{"key":"ref_39","unstructured":"(2018, June 18). Bipolar Disorder Test\u2014Scientific Test, Instant Results. Instant Results. Available online: https:\/\/psychcentral.com\/quizzes\/bipolar-quiz\/."},{"key":"ref_40","doi-asserted-by":"crossref","unstructured":"Lechevallier, Y., and Saporta, G. (2010). Large-Scale Machine Learning with Stochastic Gradient Descent. Proceedings of COMPSTAT\u20192010, Physica-Verlag HD.","DOI":"10.1007\/978-3-7908-2604-3"},{"key":"ref_41","first-page":"1","article-title":"Twitter sentiment classification using distant supervision","volume":"Volume 1","author":"Go","year":"2009","journal-title":"CS224N Project Report"},{"key":"ref_42","doi-asserted-by":"crossref","unstructured":"Wang, T., Brede, M., Ianni, A., and Mentzakis, E. (2017, January 6\u201310). Detecting and characterizing eating-disorder communities on social media. Proceedings of the Tenth ACM International Conference on Web Search and Data Mining\u2014WSDM \u201917, Cambridge, UK.","DOI":"10.1145\/3018661.3018706"},{"key":"ref_43","doi-asserted-by":"crossref","first-page":"217","DOI":"10.1109\/TAFFC.2014.2315623","article-title":"Affective and content analysis of online depression communities","volume":"5","author":"Nguyen","year":"2014","journal-title":"IEEE Trans. Affect. Comput."},{"key":"ref_44","doi-asserted-by":"crossref","unstructured":"Sumner, C., Byers, A., and Boochever, R. (2012, January 12\u201315). Predicting dark triad personality traits from Twitter usage and a linguistic analysis of tweets. Proceedings of the 11th International Conference on Machine Learning and Applications, ICMLA, Boca Raton, FL, USA.","DOI":"10.1109\/ICMLA.2012.218"},{"key":"ref_45","doi-asserted-by":"crossref","unstructured":"Wald, R., Khoshgoftaar, T.M., and Napolitano, A. (2012, January 12\u201315). Using Twitter content to predict psychopathy. Proceedings of the 2012 11th International Conference on Machine Learning and Applications, Boca Raton, FL, USA.","DOI":"10.1109\/ICMLA.2012.228"},{"key":"ref_46","doi-asserted-by":"crossref","first-page":"201","DOI":"10.1007\/978-3-642-40319-4_18","article-title":"A Depression detection model based on sentiment analysis in micro-blog social network","volume":"Volume 7867","author":"Li","year":"2013","journal-title":"Trends and Applications in Knowledge Discovery and Data Mining"},{"key":"ref_47","first-page":"185","article-title":"Rule-based and lightly supervised methods to predict emotions in suicide notes","volume":"5","author":"Pedersen","year":"2012","journal-title":"Biomed. Inform. Insights"},{"key":"ref_48","doi-asserted-by":"crossref","first-page":"2581","DOI":"10.1001\/jama.291.21.2581","article-title":"Prevalence, severity, and unmet need for treatment of mental disorders in the World Health Organization World Mental Health Surveys","volume":"291","author":"Demyttenaere","year":"2004","journal-title":"JAMA"},{"key":"ref_49","doi-asserted-by":"crossref","first-page":"93","DOI":"10.1002\/mpr.168","article-title":"The world mental health (WMH) survey initiative version of the world health organization (WHO) composite international diagnostic interview (CIDI)","volume":"13","author":"Kessler","year":"2004","journal-title":"Int. J. Methods Psychiatr. Res."},{"key":"ref_50","doi-asserted-by":"crossref","first-page":"39","DOI":"10.1145\/219717.219748","article-title":"WordNet: A lexical database for English","volume":"38","author":"Miller","year":"1995","journal-title":"Commun. ACM"},{"key":"ref_51","doi-asserted-by":"crossref","first-page":"1576","DOI":"10.2105\/AJPH.93.9.1576","article-title":"Moving to opportunity: An experimental study of neighborhood effects on mental health","volume":"93","author":"Leventhal","year":"2003","journal-title":"Am. J. Public Health"},{"key":"ref_52","doi-asserted-by":"crossref","unstructured":"Gamallo, P., and Garcia, M. (2014, January 23\u201324). Citius: A Naive-Bayes strategy for sentiment analysis on English tweets. Proceedings of the 8th International Workshop on Semantic Evaluation, Dublin, Ireland.","DOI":"10.3115\/v1\/S14-2026"},{"key":"ref_53","doi-asserted-by":"crossref","unstructured":"Chikersal, P., Poria, S., and Cambria, E. (2015, January 4\u20135). SeNTU: Sentiment analysis of tweets by combining a rule-based classifier with supervised learning. Proceedings of the 9th International Workshop on Semantic Evaluation, Denver, CO, USA.","DOI":"10.18653\/v1\/S15-2108"}],"container-title":["International Journal of Environmental Research and Public Health"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/1660-4601\/16\/6\/953\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T12:38:23Z","timestamp":1760186303000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/1660-4601\/16\/6\/953"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2019,3,16]]},"references-count":53,"journal-issue":{"issue":"6","published-online":{"date-parts":[[2019,3]]}},"alternative-id":["ijerph16060953"],"URL":"https:\/\/doi.org\/10.3390\/ijerph16060953","relation":{},"ISSN":["1660-4601"],"issn-type":[{"value":"1660-4601","type":"electronic"}],"subject":[],"published":{"date-parts":[[2019,3,16]]}}}