Understanding Depression Detection Using Social Media
Data mining; Deep learning; Diseases; Depression factor; Depression symptom; Depressive symptom; Mental health; Mental illness; Social media; Social medium mental health; Textual data; Social networking (online)
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Institute of Electrical and Electronics Engineers Inc.
2023
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my.uniten.dspace-269702023-05-29T17:38:15Z Understanding Depression Detection Using Social Media Latif A.A. Cob Z.C. Drus S.M. Anwar R.M. Radzi H.M. 46461488000 25824919900 56330463900 24721188400 57211279880 Data mining; Deep learning; Diseases; Depression factor; Depression symptom; Depressive symptom; Mental health; Mental illness; Social media; Social medium mental health; Textual data; Social networking (online) The social media is used in expressing thoughts as an act of finding release of minds and sharing social experience through digital manners. This has generated a plethora amount of data through the utilization of social media, where the data is categorized in multiple and different format. Posting made by social media users may include depressed patients where their data could be used in discovering cues or features of the mental illness. Researchers applied different techniques in using social media to discover the depression manners such as data mining, deep learning, and machine learning. Earlier studies have discovered factors that exhibits traits of depressed people by analysing the data from social media postings. This has helped to detect the depressive symptoms in individuals using textual data. The outcome of this paper is to review previous studies and evaluate the factors used to detect depression from the social media. � 2021 IEEE. Final 2023-05-29T09:38:15Z 2023-05-29T09:38:15Z 2022 Conference Paper 10.1109/ICRAIE52900.2021.9703977 2-s2.0-85136494618 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85136494618&doi=10.1109%2fICRAIE52900.2021.9703977&partnerID=40&md5=0f4d6c993d151947b9782b40f0f1d661 https://irepository.uniten.edu.my/handle/123456789/26970 Institute of Electrical and Electronics Engineers Inc. Scopus |
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Data mining; Deep learning; Diseases; Depression factor; Depression symptom; Depressive symptom; Mental health; Mental illness; Social media; Social medium mental health; Textual data; Social networking (online) |
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46461488000 |
| author_facet |
46461488000 Latif A.A. Cob Z.C. Drus S.M. Anwar R.M. Radzi H.M. |
| format |
Conference Paper |
| author |
Latif A.A. Cob Z.C. Drus S.M. Anwar R.M. Radzi H.M. |
| spellingShingle |
Latif A.A. Cob Z.C. Drus S.M. Anwar R.M. Radzi H.M. Understanding Depression Detection Using Social Media |
| author_sort |
Latif A.A. |
| title |
Understanding Depression Detection Using Social Media |
| title_short |
Understanding Depression Detection Using Social Media |
| title_full |
Understanding Depression Detection Using Social Media |
| title_fullStr |
Understanding Depression Detection Using Social Media |
| title_full_unstemmed |
Understanding Depression Detection Using Social Media |
| title_sort |
understanding depression detection using social media |
| publisher |
Institute of Electrical and Electronics Engineers Inc. |
| publishDate |
2023 |
| _version_ |
1806423428986568704 |