This paper is in the following e-collection/theme issue:

Medicine 2.0: Social Media, Open, Participatory, Collaborative Medicine (1641) Infodemiology and Infoveillance (1349) Depression and Mood Disorders; Suicide Prevention (1363) Ontologies, Classifications, and Coding (239) Infoveillance, Infodemiology, Digital Disease Surveillance, Infodemic Management (1041)

Published on in Vol 19, No 7 (2017): July

Ontology-Based Approach to Social Data Sentiment Analysis: Detection of Adolescent Depression Signals

Ontology-Based Approach to Social Data Sentiment Analysis: Detection of Adolescent Depression Signals

Ontology-Based Approach to Social Data Sentiment Analysis: Detection of Adolescent Depression Signals

Authors of this article:

Hyesil Jung1 Author Orcid Image ;   Hyeoun-Ae Park1 Author Orcid Image ;   Tae-Min Song2 Author Orcid Image
Article Authors Cited by (40) Tweetations (9) Metrics

Journals

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  2. Mavragani A. Infodemiology and Infoveillance: Scoping Review. Journal of Medical Internet Research 2020;22(4):e16206 View
  3. On J, Park H, Song T. Sentiment Analysis of Social Media on Childhood Vaccination: Development of an Ontology. Journal of Medical Internet Research 2019;21(6):e13456 View
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  7. Zunic A, Corcoran P, Spasic I. Sentiment Analysis in Health and Well-Being: Systematic Review. JMIR Medical Informatics 2020;8(1):e16023 View
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  9. Castillo-Sánchez G, Marques G, Dorronzoro E, Rivera-Romero O, Franco-Martín M, De la Torre-Díez I. Suicide Risk Assessment Using Machine Learning and Social Networks: a Scoping Review. Journal of Medical Systems 2020;44(12) View
  10. Lee J, Lee J, Park S. An Ontology of Intimate Partnerships for Social Big Data Research. Journal of Families and Better Life 2020;38(4):1 View
  11. Rassy J, Bardon C, Dargis L, Côté L, Corthésy-Blondin L, Mörch C, Labelle R. Information and Communication Technology Use in Suicide Prevention: Scoping Review. Journal of Medical Internet Research 2021;23(5):e25288 View
  12. Dragos V, Battistelli D, Kellodjoue E. A formal representation of appraisal categories for social data analysis. Procedia Computer Science 2020;176:928 View
  13. Lee J, Park H, Park S, Song T. Using Social Media Data to Understand Consumers' Information Needs and Emotions Regarding Cancer: Ontology-Based Data Analysis Study. Journal of Medical Internet Research 2020;22(12):e18767 View
  14. Chiong R, Budhi G, Dhakal S, Chiong F. A textual-based featuring approach for depression detection using machine learning classifiers and social media texts. Computers in Biology and Medicine 2021;135:104499 View
  15. Lee J, Park H, Song T. A Determinants-of-Fertility Ontology for Detecting Future Signals of Fertility Issues From Social Media Data: Development of an Ontology. Journal of Medical Internet Research 2021;23(6):e25028 View
  16. Arias F, Zambrano Nunez M, Guerra-Adames A, Tejedor-Flores N, Vargas-Lombardo M. Sentiment Analysis of Public Social Media as a Tool for Health-Related Topics. IEEE Access 2022;10:74850 View
  17. Lokala U, Lamy F, Daniulaityte R, Gaur M, Gyrard A, Thirunarayan K, Kursuncu U, Sheth A. Drug Abuse Ontology to Harness Web-Based Data for Substance Use Epidemiology Research: Ontology Development Study. JMIR Public Health and Surveillance 2022;8(12):e24938 View
  18. Dias L, Vianna H, Barbosa J. Human behaviour data analysis and noncommunicable diseases: a systematic mapping study. Behaviour & Information Technology 2023;42(14):2485 View
  19. Guo J, Keeshin B, Conway M, Chapman W, Sward K. A Scoping Review and Content Analysis of Common Depressive Symptoms of Young People. The Journal of School Nursing 2022;38(1):74 View
  20. Mullick T, Radovic A, Shaaban S, Doryab A. Predicting Depression in Adolescents Using Mobile and Wearable Sensors: Multimodal Machine Learning–Based Exploratory Study. JMIR Formative Research 2022;6(6):e35807 View
  21. Yang S, Huang P, Li B, Gan T, Lin W, Liu Y. The relationship of negative life events, trait-anxiety and depression among Chinese university students: A moderated effect of self-esteem. Journal of Affective Disorders 2023;339:384 View
  22. Królak A, Wiktorski T, Żmudzińska A. Automatic analysis of X (Twitter) data for supporting depression diagnosis. Human Technology 2023;19(3):370 View
  23. Zhang W, Kong L, Lee S, Chen Y, Zhang G, Wang H, Song M. Detecting mental and physical disorders using multi-task learning equipped with knowledge graph attention network. Artificial Intelligence in Medicine 2024;149:102812 View
  24. Zhang W, Xie J, Zhang Z, Liu X. Depression Detection Using Digital Traces on Social Media: A Knowledge-aware Deep Learning Approach. Journal of Management Information Systems 2024;41(2):546 View
  25. Dalal S, Jain S, Dave M. DepressionFeature: Underlying ontology for user-specific depression analysis. The Journal of Supercomputing 2025;81(1) View

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  1. Wang D, Xu L, Younas A. Machine Learning and Data Mining in Pattern Recognition. View
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