Published on 10.03.16 in Vol 18, No 3 (2016): March
Works citing "Understanding Online Health Groups for Depression: Social Network and Linguistic Perspectives"
According to Crossref, the following articles are citing this article (DOI 10.2196/jmir.5042):
(note that this is only a small subset of citations)
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Moyano AN, Sicilia MA, Barriocanal EG. On the Graph Structure of the Web of Data. International Journal on Semantic Web and Information Systems 2018;14(2):70
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Moessner M, Feldhege J, Wolf M, Bauer S. Analyzing big data in social media: Text and network analyses of an eating disorder forum. International Journal of Eating Disorders 2018;51(7):656
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Yao X, Yu G, Tian X, Tang J. Patterns and Longitudinal Changes in Negative Emotions of People with Depression on Sina Weibo. Telemedicine and e-Health 2020;26(6):734
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Li Y, Cai M, Qin S, Lu X. Depressive Emotion Detection and Behavior Analysis of Men Who Have Sex With Men via Social Media. Frontiers in Psychiatry 2020;11
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Shrestha A, Serra E, Spezzano F. Multi-modal social and psycho-linguistic embedding via recurrent neural networks to identify depressed users in online forums. Network Modeling Analysis in Health Informatics and Bioinformatics 2020;9(1)
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Wang X, Zhao K, Zhou X, Street N. Predicting User Posting Activities in Online Health Communities with Deep Learning. ACM Transactions on Management Information Systems 2020;11(3):1
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Bailey S, Zhang Y, Ramesh A, Golbeck J, Getoor L. A Structured and Linguistic Approach to Understanding Recovery and Relapse in AA. ACM Transactions on the Web 2021;15(1):1
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Baptista N, Pinho JC, Alves H. Social Marketing and Online Social Support Structure in Contexts of Treatment Uncertainty. Journal of Nonprofit & Public Sector Marketing 2022;34(3):311
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Yao X, Yu G, Tang J, Zhang J. Extracting depressive symptoms and their associations from an online depression community. Computers in Human Behavior 2021;120:106734
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Ramamoorthy T, Karmegam D, Mappillairaju B. Use of social media data for disease based social network analysis and network modeling: A Systematic Review. Informatics for Health and Social Care 2021;46(4):443
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HUANG G, ZHOU X. The linguistic patterns of depressed patients. Advances in Psychological Science 2021;29(5):838
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Ghosh S, Anwar T. Depression Intensity Estimation via Social Media: A Deep Learning Approach. IEEE Transactions on Computational Social Systems 2021;8(6):1465
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Storman D, Jemioło P, Swierz MJ, Sawiec Z, Antonowicz E, Prokop-Dorner A, Gotfryd-Burzyńska M, Bala MM. Meeting the Unmet Needs of Individuals With Mental Disorders: Scoping Review on Peer-to-Peer Web-Based Interactions. JMIR Mental Health 2022;9(12):e36056
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Belz FF, Adair KC, Proulx J, Frankel AS, Sexton JB. The language of healthcare worker emotional exhaustion: A linguistic analysis of longitudinal survey. Frontiers in Psychiatry 2022;13
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Zhong D, Liu C, Luan C, Li W, Cui J, Shi H, Zhang Q. Mental health problems among healthcare professionals following the workplace violence issue-mediating effect of risk perception. Frontiers in Psychology 2022;13
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Pan W, Wang X, Zhou W, Hang B, Guo L. Linguistic Analysis for Identifying Depression and Subsequent Suicidal Ideation on Weibo: Machine Learning Approaches. International Journal of Environmental Research and Public Health 2023;20(3):2688
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Shi J, Khoo Z. Online health community for change: Analysis of self-disclosure and social networks of users with depression. Frontiers in Psychology 2023;14
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Hards E, Orchard F, Reynolds S. ‘I am tired, sad and kind’: self-evaluation and symptoms of depression in adolescents. Child and Adolescent Psychiatry and Mental Health 2023;17(1)
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Lu Y, Wang X, Su L, Zhao H. Multiplex Social Network Analysis to Understand the Social Engagement of Patients in Online Health Communities. Mathematics 2023;11(21):4412
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Shi J, Khoo Z. Words for the hearts: a corpus study of metaphors in online depression communities. Frontiers in Psychology 2023;14
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Humayun MM, Brouillette M, Fellows LK, Mayo NE. The Patient Generated Index (PGI) as an early-warning system for predicting brain health challenges: a prospective cohort study for people living with Human Immunodeficiency Virus (HIV). Quality of Life Research 2023;32(12):3439
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Wang X, Zhao K, Amato MS, Stanton CA, Shuter J, Graham AL. The Role of Seed Users in Nurturing an Online Health Community for Smoking Cessation Among People With HIV/AIDS. Annals of Behavioral Medicine 2024;58(2):122
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Li S, Pan W, Yip PSF, Wang J, Zhou W, Zhu T. Uncovering the heterogeneous effects of depression on suicide risk conditioned by linguistic features: A double machine learning approach. Computers in Human Behavior 2024;152:108080
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Wu X, Zhou Y, Zhong B. Measuring social support for depression on social media: A multifaceted study on user interaction and emotional spread. Telematics and Informatics 2024;89:102120
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Zhang Z, Li Z, Zhu J, Guo Z, Shi B, Hu B. Enhancing user sequence representation with cross-view collaborative learning for depression detection on Sina Weibo. Knowledge-Based Systems 2024;293:111650
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According to Crossref, the following books are citing this article (DOI 10.2196/jmir.5042):
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Xu R, Zhou J, Zhang Q, Hendler JA. Encyclopedia of Social Network Analysis and Mining. 2017. Chapter 110215-1:1
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Xu R, Zhou J, Zhang Q, Hendler JA. Encyclopedia of Social Network Analysis and Mining. 2018. Chapter 110215:2239
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Gui T, Zhang Q, Zhu L, Zhou X, Peng M, Huang X. Chinese Computational Linguistics. 2019. Chapter 49:613
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. Proceedings of 2nd International Conference on Artificial Intelligence: Advances and Applications. 2022. Chapter 1:1
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