Mapping and Visualizing the Intersection of Sentiment Analysis and Mental Health
DOI:
https://doi.org/10.56294/sctconf20251543Keywords:
Sentiment Analysis, Mental Health, Bibliometric Analysis, Biblioshiny, VOSviewer, CitespaceAbstract
Introduction: Sentiment analysis, a computational approach to evaluating emotions in textual data, has gained significance in mental health research. It assesses public sentiments on mental health issues and aids in early disorder detection through social media and digital platforms.
Objectives: This study aims to analyze the intersection of sentiment analysis and mental health research, identifying key scholarly trends, thematic developments, and global collaborations from 2013 to 2024.
Methods: A bibliometric analysis was conducted using 521 documents from Scopus, including journal articles, book chapters, and conference papers. Biblioshiny, VOSviewer, and CiteSpace were used to analyze publication trends, co-authorship networks, and keyword co-occurrences.
Results: The field has grown at an annual rate of 42.45%, with research output peaking in 2023 (134 articles). Key themes include AI applications in mental health, sentiment-based diagnosis, and the impact of COVID-19. China, the USA, and Australia are the leading contributors, while Bangladesh and Switzerland have the highest citation impact per article. The study maps extensive international research collaborations.
Conclusions: Sentiment analysis is an evolving field with global collaboration. Advances in machine learning and NLP enhance its potential for real-time mental health monitoring and predictive analysis. Future research should focus on personalized AI-driven interventions, ethical considerations, and expanding datasets to improve diagnostic accuracy. This study provides insights for researchers, practitioners, and policymakers in leveraging sentiment analysis for mental health advancements.
References
1. Kakde P. Sentimental Analysis Using Machine Learning for Mental Healthcare Management System. International Journal for Research in Applied Science and Engineering Technology 2023;
2. Verma R, Nipun, Rana N, Arora DRK. Mental Health Prediction using Sentimental Analysis. International Journal for Research in Applied Science and Engineering Technology 2023;
3. Zhang J. An Overview of the Application of Sentiment Analysis in Mental Well-being. Applied and Computational Engineering 2023;
4. Fatima T, Malik SA, Shabbir A. Hospital healthcare service quality, patient satisfaction and loyalty. International Journal of Quality & Reliability Management 2018;
5. Provoost S, Ruwaard J, Breda W van, Riper H, Bosse T. Validating Automated Sentiment Analysis of Online Cognitive Behavioral Therapy Patient Texts: An Exploratory Study. Frontiers in Psychology 2019;10.
6. Shickel B, Heesacker M, Benton S, Rashidi P. Automated Emotional Valence Prediction in Mental Health Text via Deep Transfer Learning. 2020 IEEE 20th International Conference on Bioinformatics and Bioengineering (BIBE) 2020;269–74.
7. Saraff S, Taraban R, Rishipal R, Biswal R, Kedas S, Gupta S. Application of Sentiment Analysis in Understanding Human Emotions and Behaviour. EAI Endorsed Transactions on Smart Cities 2018;
8. Dixit R, Chawla G, Bajaj I. Mental Health Monitoring using Sentiment Analysis. International Journal of Scientific Research in Computer Science, Engineering and Information Technology 2022;
9. Zucco C, Calabrese B, Cannataro M. Sentiment analysis and affective computing for depression monitoring. 2017 IEEE International Conference on Bioinformatics and Biomedicine (BIBM) 2017;1988–95.
10. Srivastava M, Singh I, Khanna ES, Srivastava DAK. DEPRESSION DETECTION AND SENTIMENTS ANALYSIS. INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT 2023;
11. Nandwani P, Verma R. A review on sentiment analysis and emotion detection from text. Social Network Analysis and Mining 2021;11.
12. Cherian S, Joseph J, Thomas B, Jose J. Navigating the New Normal: A Bibliometric Analysis of Masked Face Recognition Research Using VOSviewer and Biblioshiny.
13. John J, Joseph J, Mathew L, James S, Jose J. Exploring the Predictive Analytics Frontier in Business: A Bibliometric Journey. J Scientometric Res 2024;13(2):365–81.
14. Abbas A, Jusoh A, Mas’od A, Ali J, Alsharif A, Alharthi R. A BIBLIOMETRIC ANALYSIS of PUBLICATIONS on SOCIAL MEDIA INFLUENCERS USING VOSVIEWER. Journal of Theoretical and Applied Information Technology 2021;99:5662–76.
15. Agac G, Sevim F, Celik O, Bostan S, Erdem R, Yalcin YI. Research hotspots, trends and opportunities on the metaverse in health education: a bibliometric analysis. LHT [Internet] 2023 [cited 2023 Sep 26];Available from: https://www.emerald.com/insight/content/doi/10.1108/LHT-04-2023-0168/full/html
16. Barbu L. Global trends in the scientific research of the health economics: a bibliometric analysis from 1975 to 2022. Health Econ Rev 2023;13(1):31.
17. Joseph J, Thomas B, Jose J, Pathak N. Decoding the growth of multimodal learning: A bibliometric exploration of its impact and influence. Int Dec Tech 2024;18(1):151–67.
18. Thomas B, Joseph J, Jose J. Explorative Bibliometric Study of Medical Image Analysis: Unveiling Trends and Advancements. SV 2023;15(5):35–49.
19. Agbo FJ, Oyelere SS, Suhonen J, Tukiainen M. Scientific production and thematic breakthroughs in smart learning environments: a bibliometric analysis. Smart Learning Environments 2021;8(1):1.
20. do Carmo G, Felizardo LF, de Castro Alcântara V, da Silva CA, do Prado JW. The impact of Jürgen Habermas’s scientific production: a scientometric review. Scientometrics 2023;128(3):1853–75.
21. Godin B. On the origins of bibliometrics. Scientometrics 2006;68(1):109–33.
22. Devaki V, Ramganesh DE, Amutha DS. Bibliometric Analysis on Metacognition and Self-Regulation Using Biblioshiny Software. Indian Journal of Information Sources and Services 2024;14(2):115–25.
23. Thangavel P, Chandra B. Two decades of M-commerce consumer research: A bibliometric analysis using R biblioshiny. Sustainability 2023;15(15):11835.
24. Joseph J, Kartheeban K. Visualizing the Impact of Machine Learning on Cardiovascular Disease Prediction: A Comprehensive Analysis of Research Trends. SV 2024;16(5):1–21.
25. Joseph J, Jose J, John D, Nair SV. QUANTIFYING THE IMPACT OF WEARABLE HEALTH MONITORING AND MACHINE LEARNING RESEARCH: A BIBLIOMETRIC ANALYSIS. . Vol 2023;(19).
26. Joseph J, Jose J, Jose AS, Ettaniyil GG, Nair SV. A scientometric analysis of bibliotherapy: mapping the research landscape. Library Hi Tech [Internet] 2024 [cited 2024 Oct 9];ahead-of-print(ahead-of-print). Available from: https://doi.org/10.1108/LHT-08-2023-0341
27. Joseph J, Jose J, Jose AS, Ettaniyil GG, Cyriac J, Sebastian SK, et al. Quantitative insights into outcome-based education: a bibliometric exploration. IJERE 2024;13(6):4030.
28. Joseph J, Jose J, Jose AS, Ettaniyil GG, John J, Nellanat PD. UNVEILING THE RESEARCH IMPACT: A VISUALIZATION STUDY OF CHATGPT’S INFLUENCE ON THE SCIENTIFIC LANDSCAPE. . Vol 2023;(22).
29. Arruda H, Silva ER, Lessa M, Proença Jr D, Bartholo R. VOSviewer and bibliometrix. Journal of the Medical Library Association: JMLA 2022;110(3):392.
30. Ejaz H, Zeeshan HM, Ahmad F, Bukhari SNA, Anwar N, Alanazi A, et al. Bibliometric analysis of publications on the omicron variant from 2020 to 2022 in the Scopus database using R and VOSviewer. International Journal of Environmental Research and Public Health 2022;19(19):12407.
31. Jumansyah R, Soegoto ES, Albar CN. COMPUTATIONAL BIBLIOMETRIC ANALYSIS OF EVOLUTIONARY GAME THEORY (EGT) RESEARCH USING VOSVIEWER. 2023;18.
32. Fauzan TA, Soegoto ES. COMPUTATIONAL BIBLIOMETRIC ANALYSIS OF EDUCATION TECHNOLOGY USING VOSVIEWER APPLICATION WITH PUBLISH OR PERISH (USING GOOGLE SCHOLAR DATA). 2023;18.
33. Maryanti R, Nandiyanto ABD, Hufad A, Sunardi S, Husaeni DNA, Husaeni DFA. A COMPUTATIONAL BIBLIOMETRIC ANALYSIS OF SCIENCE EDUCATION RESEARCH USING VOSVIEWER. 2023;18.
34. van Eck NJ, Waltman L. Software survey: VOSviewer, a computer program for bibliometric mapping. Scientometrics 2010;84(2):523–38.
35. Guleria D, Kaur G. Bibliometric analysis of ecopreneurship using VOSviewer and RStudio Bibliometrix, 1989–2019. Library Hi Tech 2021;39(4):1001–24.
36. Geng Y, Zhang X, Gao J, Yan Y, Chen L. Bibliometric analysis of sustainable tourism using CiteSpace. Technological Forecasting and Social Change 2024;202:123310.
37. Synnestvedt M, Chen C, Holmes J. CiteSpace II: Visualization and Knowledge Discovery in Bibliographic Databases. AMIA . Annual Symposium proceedings / AMIA Symposium AMIA Symposium 2005;2005:724–8.
38. Niazi MA. Review of “CiteSpace: A Practical Guide For Mapping Scientific Literature” by Chaomei Chen. Complex Adaptive Systems Modeling 2016;4(1):23.
39. Sun W, Wu W, Dong X, Yu G. Frontier and hot topics in the application of hydrogel in the biomedical field: a bibliometric analysis based on CiteSpace. J Biol Eng 2024;18(1):40.
Downloads
Published
Issue
Section
License
Copyright (c) 2025 Jobin Varghese P , Anna Paul , Jaya Cherian , Jeena Joseph , Ajesh P Joseph , Jose Joseph , Athullya Sebastian (Author)
This work is licensed under a Creative Commons Attribution 4.0 International License.
The article is distributed under the Creative Commons Attribution 4.0 License. Unless otherwise stated, associated published material is distributed under the same licence.
