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

Digital Health Reviews (1724) Digital Mental Health Interventions, e-Mental Health and Cyberpsychology (2111) Infoveillance, Infodemiology, Digital Disease Surveillance, Infodemic Management (1139) Big Data (307)

Published on in Vol 25 (2023)

This is a member publication of University of Bristol (Jisc)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/42734, first published .
Methodologies for Monitoring Mental Health on Twitter: Systematic Review

Methodologies for Monitoring Mental Health on Twitter: Systematic Review

Methodologies for Monitoring Mental Health on Twitter: Systematic Review

Authors of this article:

Nina H Di Cara1, 2 Author Orcid Image ;   Valerio Maggio2, 3 Author Orcid Image ;   Oliver S P Davis2, 3, 4 Author Orcid Image ;   Claire M A Haworth1, 4 Author Orcid Image
Article Authors Cited by (28) Tweetations (6) Metrics

Journals

  1. Thakur N. Sentiment Analysis and Text Analysis of the Public Discourse on Twitter about COVID-19 and MPox. Big Data and Cognitive Computing 2023;7(2):116 View
  2. McGarry K. Analyzing Social Media Data Using Sentiment Mining and Bigram Analysis for the Recommendation of YouTube Videos. Information 2023;14(7):408 View
  3. Colella S, Dufourt F, Hildebrand V, Vivès R. Mental health effects of COVID-19 lockdowns: A Twitter-based analysis. Economics & Human Biology 2023;51:101307 View
  4. Wang Y, Deng H, Gao S, Li T, Wang F. A Fresh Perspective on Examining Population Emotional Well-Being Trends by Internet Search Engine: An Emerging Composite Anxiety and Depression Index. International Journal of Environmental Research and Public Health 2024;21(2):202 View
  5. Florath J, Chanussot J, Keller S. Road Accessibility during Natural Hazards Based on Volunteered Geographic Information Data and Network Analysis. ISPRS International Journal of Geo-Information 2024;13(4):107 View
  6. Zhu Z. Maternal mental health monitoring in an online community: a natural language processing approach. Behaviour & Information Technology 2025;44(10):2379 View
  7. Benjachairat P, Senivongse T, Taephant N, Puvapaisankit J, Maturosjamnan C, Kultananawat T. Classification of suicidal ideation severity from Twitter messages using machine learning. International Journal of Information Management Data Insights 2024;4(2):100280 View
  8. Merayo N, Ayuso-Lanchares A, González-Sanguino C. Machine learning and natural language processing to assess the emotional impact of influencers’ mental health content on Instagram. PeerJ Computer Science 2024;10:e2251 View
  9. Bokolo B, Liu Q. Advanced Comparative Analysis of Machine Learning and Transformer Models for Depression and Suicide Detection in Social Media Texts. Electronics 2024;13(20):3980 View
  10. Di Cara N, Joinson D, Mummé M, Tanner A, Maggio V, Thomas R, Haworth C, Boyd A, Davis O. Twitter data as a linked digital phenotype in the Avon Longitudinal Study of Parents and Children. Wellcome Open Research 2024;9:688 View
  11. Bonnevie E, Smith S, Kapur M, Smyser J, Castrucci B. Leveraging Media Monitoring to Inform Targeted Health Communications for Adolescents, Older Adults, and LGBTQ+ People. Journal of Public Health Management & Practice 2025;31(4):614 View
  12. Lien Y, Feng H, Tseng Y, Chen C, Tseng W. Exploring mental health literacy on twitter: A machine learning approach. Journal of Affective Disorders 2025;382:296 View
  13. Naseriparsa M, Sukunesan S, Cai Z, Alfarraj O, Tolba A, Fathi Rabooki S, Xia F. ED-Filter: dynamic feature filtering for eating disorder classification. Artificial Intelligence Review 2025;58(8) View
  14. John J, Prathap B, Gupta G, Melanaturu J. Categorizing Mental Stress: A Consistency-Focused Benchmarking of ML and DL Models for Multi-Label, Multi-Class Classification via Taxonomy-Driven NLP Techniques. Natural Language Processing Journal 2025;11:100162 View
  15. Almeraj Z, Husain F, Arriaga R. A Cross-Cultural/Lingual Natural Language Processing Analysis of Disability Awareness on Social Media. IEEE Access 2025;13:110128 View
  16. Dhanda S, Panwar D, Lin C, Sharma T, Rastogi D, Bindewari S, Singh A, Li Y, Agarwal N, Agarwal S. Advancement in public health through machine learning: a narrative review of opportunities and ethical considerations. Journal of Big Data 2025;12(1) View
  17. Kim D, Magane R, Poitier M, Kuang J, Wang A, Adderley R, Deveaux L. Social media use, risk behavior engagement, and mental health among middle adolescents in the Caribbean. BMC Public Health 2025;25(1) View
  18. Joinson D, Haworth C, Simpson E, Cristianini N, Di Cara N, Davis O. Active night-time tweeting is associated with meaningfully lower mental wellbeing in a UK birth cohort study. Scientific Reports 2025;15(1) View
  19. Zheng Y, Chen X, Zhang M, Zhu R, Jin Y. Darker nights, happier lives? The impact of urban green space night-time accessibility on residents' subjective happiness: A case study of the main urban area of Hangzhou. Cities 2026;169:106510 View
  20. Merayo N, Ayuso-Lanchares A, González-Sanguino C. Revealing Emotional Insights From Mental Health Discussions on Instagram and TikTok Using BERT Models. IEEE Transactions on Affective Computing 2025;16(4):3279 View

Books/Policy Documents

  1. Haldar S, El-Gayar O, El-Gayar S. Impact of Digital Solutions for Improved Healthcare Delivery. View
  2. Chatterjee S, Dindarian A, Rengaraju U. Revolutionizing Youth Mental Health with Ethical AI. View
  3. Zhu Z. Artificial Intelligence in Healthcare. View

Conference Proceedings

  1. Ge Z, Hu N, Li D, Wang Y, Qi S, Xu Y, Shi H, Zhang J. 2025 IEEE 41st International Conference on Data Engineering Workshops (ICDEW). A Survey of Large Language Models in Mental Health Disorder Detection on Social Media View
  2. Rana A, Prajoga T, Nathani P, Qomariyah N, Bahana R. 2025 International Conference on Information and Communication Technology (ICoICT). Evaluating Mental Health Awareness on TikTok and Twitter with Sentiment Analysis and XGBoost View
  3. AlMeraj Z, Husain F, Arriaga R. Companion Publication of the 2025 Conference on Computer-Supported Cooperative Work and Social Computing. From Hashtag to Human-Centered Insights: Rethinking Disability Awareness Across Languages View
  4. Fauzi L, Setiawan E. 2025 IEEE International Symposium on Future Telecommunication Technologies (SOFTT). Hybrid CNN-BiLSTM with GloVe, Word2Vec, and Attention Mechanism for Multimodal Sentiment Analysis in Mental Health View
  5. K R, Rananavare L. 2025 IEEE International Conference on Distributed Computing, VLSI, Electrical Circuits and Robotics (DISCOVER). A Comprehensive Survey on Depression Detection Through Social Media Using Machine Learning and NLP Techniques View