A survey on detecting mental disorders with natural language processing: Literature review, trends and challenges

For years, the scientific community has researched monitoring approaches for the detection of certain mental disorders and risky behaviors, like depression, eating disorders, gambling, and suicidal ideation among others, in order to activate prevention or mitigation strategies and, in severe cases,...

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Detalles Bibliográficos
Autores: Montejo Ráez, Arturo, Molina González, M. Dolores, Jiménez Zafra, Salud María, García Cumbreras, Miguel Ángel, García López, Luis Joaquín
Tipo de recurso: artículo
Estado:Versión publicada
Fecha de publicación:2024
País:España
Institución:Universidad de Jaén
Repositorio:RUJA. Repositorio Institucional de la Producción Científica de la Universidad de Jaén
OAI Identifier:oai:ruja.ujaen.es:10953/7457
Acceso en línea:https://doi.org/10.1016/j.cosrev.2024.100654
https://www.sciencedirect.com/science/article/pii/S1574013724000388
https://hdl.handle.net/10953/7457
Access Level:acceso abierto
Palabra clave:Mental disorders detection
Natural language processing
Machine learning
Survey
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spelling A survey on detecting mental disorders with natural language processing: Literature review, trends and challengesMontejo Ráez, ArturoMolina González, M. DoloresJiménez Zafra, Salud MaríaGarcía Cumbreras, Miguel ÁngelGarcía López, Luis JoaquínMental disorders detectionNatural language processingMachine learningSurvey004004.6004.8004.91616.89For years, the scientific community has researched monitoring approaches for the detection of certain mental disorders and risky behaviors, like depression, eating disorders, gambling, and suicidal ideation among others, in order to activate prevention or mitigation strategies and, in severe cases, clinical treatment. Natural Language Processing is one of the most active disciplines dealing with the automatic detection of mental disorders. This paper offers a comprehensive and extensive review of research works on Natural Language Processing applied to the identification of some mental disorders. To this end, we have identified from a literature review, which are the main types of features used to represent the texts, the machine learning algorithms that are preferred or the most targeted social media platforms, among other aspects. Besides, the paper reports on scientific forums and projects focused on the automatic detection of these problems over the most popular social networks. Thus, this compilation provides a broad view of the matter, summarizing main strategies, and significant findings, but, also, recognizing some of the weaknesses in the research works published so far, serving as clues for future research.Elsevier202620262024info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionapplication/pdfhttps://doi.org/10.1016/j.cosrev.2024.100654https://www.sciencedirect.com/science/article/pii/S1574013724000388https://hdl.handle.net/10953/7457reponame:RUJA. Repositorio Institucional de la Producción Científica de la Universidad de Jaéninstname:Universidad de JaénInglésComputer Science ReviewAttribution-NonCommercial-NoDerivs 3.0 Spainhttp://creativecommons.org/licenses/by-nc-nd/3.0/es/info:eu-repo/semantics/openAccessoai:ruja.ujaen.es:10953/74572026-06-24T12:41:07Z
dc.title.none.fl_str_mv A survey on detecting mental disorders with natural language processing: Literature review, trends and challenges
title A survey on detecting mental disorders with natural language processing: Literature review, trends and challenges
spellingShingle A survey on detecting mental disorders with natural language processing: Literature review, trends and challenges
Montejo Ráez, Arturo
Mental disorders detection
Natural language processing
Machine learning
Survey
004
004.6
004.8
004.91
616.89
title_short A survey on detecting mental disorders with natural language processing: Literature review, trends and challenges
title_full A survey on detecting mental disorders with natural language processing: Literature review, trends and challenges
title_fullStr A survey on detecting mental disorders with natural language processing: Literature review, trends and challenges
title_full_unstemmed A survey on detecting mental disorders with natural language processing: Literature review, trends and challenges
title_sort A survey on detecting mental disorders with natural language processing: Literature review, trends and challenges
dc.creator.none.fl_str_mv Montejo Ráez, Arturo
Molina González, M. Dolores
Jiménez Zafra, Salud María
García Cumbreras, Miguel Ángel
García López, Luis Joaquín
author Montejo Ráez, Arturo
author_facet Montejo Ráez, Arturo
Molina González, M. Dolores
Jiménez Zafra, Salud María
García Cumbreras, Miguel Ángel
García López, Luis Joaquín
author_role author
author2 Molina González, M. Dolores
Jiménez Zafra, Salud María
García Cumbreras, Miguel Ángel
García López, Luis Joaquín
author2_role author
author
author
author
dc.subject.none.fl_str_mv Mental disorders detection
Natural language processing
Machine learning
Survey
004
004.6
004.8
004.91
616.89
topic Mental disorders detection
Natural language processing
Machine learning
Survey
004
004.6
004.8
004.91
616.89
description For years, the scientific community has researched monitoring approaches for the detection of certain mental disorders and risky behaviors, like depression, eating disorders, gambling, and suicidal ideation among others, in order to activate prevention or mitigation strategies and, in severe cases, clinical treatment. Natural Language Processing is one of the most active disciplines dealing with the automatic detection of mental disorders. This paper offers a comprehensive and extensive review of research works on Natural Language Processing applied to the identification of some mental disorders. To this end, we have identified from a literature review, which are the main types of features used to represent the texts, the machine learning algorithms that are preferred or the most targeted social media platforms, among other aspects. Besides, the paper reports on scientific forums and projects focused on the automatic detection of these problems over the most popular social networks. Thus, this compilation provides a broad view of the matter, summarizing main strategies, and significant findings, but, also, recognizing some of the weaknesses in the research works published so far, serving as clues for future research.
publishDate 2024
dc.date.none.fl_str_mv 2024
2026
2026
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
format article
status_str publishedVersion
dc.identifier.none.fl_str_mv https://doi.org/10.1016/j.cosrev.2024.100654
https://www.sciencedirect.com/science/article/pii/S1574013724000388
https://hdl.handle.net/10953/7457
url https://doi.org/10.1016/j.cosrev.2024.100654
https://www.sciencedirect.com/science/article/pii/S1574013724000388
https://hdl.handle.net/10953/7457
dc.language.none.fl_str_mv Inglés
language_invalid_str_mv Inglés
dc.relation.none.fl_str_mv Computer Science Review
dc.rights.none.fl_str_mv Attribution-NonCommercial-NoDerivs 3.0 Spain
http://creativecommons.org/licenses/by-nc-nd/3.0/es/
info:eu-repo/semantics/openAccess
rights_invalid_str_mv Attribution-NonCommercial-NoDerivs 3.0 Spain
http://creativecommons.org/licenses/by-nc-nd/3.0/es/
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv Elsevier
publisher.none.fl_str_mv Elsevier
dc.source.none.fl_str_mv reponame:RUJA. Repositorio Institucional de la Producción Científica de la Universidad de Jaén
instname:Universidad de Jaén
instname_str Universidad de Jaén
reponame_str RUJA. Repositorio Institucional de la Producción Científica de la Universidad de Jaén
collection RUJA. Repositorio Institucional de la Producción Científica de la Universidad de Jaén
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