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Citing this Article

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Published on 08.05.18 in Vol 20, No 5 (2018): May

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

Works citing "Predicting Depression From Language-Based Emotion Dynamics: Longitudinal Analysis of Facebook and Twitter Status Updates"

Elizabeth M Seabrook, Margaret L Kern, Ben D Fulcher, Nikki S Rickard

J Med Internet Res 2018 (May 08); 20(5):e168 

According to Crossref, the following articles are citing this article (DOI 10.2196/jmir.9267):

(note that this is only a small subset of citations)

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  5. Cole DA, Nick EA, Varga G, Smith D, Zelkowitz RL, Ford MA, Lédeczi . Are Aspects of Twitter Use Associated with Reduced Depressive Symptoms? The Moderating Role of In-Person Social Support. Cyberpsychology, Behavior, and Social Networking 2019;22(11):692
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  6. Burdick L, Mihalcea R, Boyd RL, Pennebaker JW. Analyzing Connections Between User Attributes, Images, and Text. Cognitive Computation 2021;13(2):241
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  7. Leis A, Ronzano F, Mayer MA, Furlong LI, Sanz F. Detecting Signs of Depression in Tweets in Spanish: Behavioral and Linguistic Analysis. Journal of Medical Internet Research 2019;21(6):e14199
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  8. Danina M, Kiselnikova N, Kuminskaya E, Lavrova E, Greskova P. Methods for Preventing Depression on Digital Platforms and in Social Media. Clinical Psychology and Special Education 2019;8(3):101
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  11. . Infodemiology and Infoveillance: Scoping Review. Journal of Medical Internet Research 2020;22(4):e16206
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  12. Tang J, Yu G, Yao X. A Comparative Study of Online Depression Communities in China. International Journal of Environmental Research and Public Health 2020;17(14):5023
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  13. . Digital health data-driven approaches to understand human behavior. Neuropsychopharmacology 2021;46(1):191
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  14. 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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  15. Stirling E, Willcox J, Ong K, Forsyth A. Social media analytics in nutrition research: a rapid review of current usage in investigation of dietary behaviours. Public Health Nutrition 2021;24(6):1193
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  16. Dwyer A, de Almeida Neto A, Estival D, Li W, Lam-Cassettari C, Antoniou M. Suitability of Text-Based Communications for the Delivery of Psychological Therapeutic Services to Rural and Remote Communities: Scoping Review. JMIR Mental Health 2021;8(2):e19478
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  17. Kim J, Uddin ZA, Lee Y, Nasri F, Gill H, Subramanieapillai M, Lee R, Udovica A, Phan L, Lui L, Iacobucci M, Mansur RB, Rosenblat JD, McIntyre RS. A Systematic review of the validity of screening depression through Facebook, Twitter, Instagram, and Snapchat. Journal of Affective Disorders 2021;286:360
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  18. Linton MA, Jelbert S, Kidger J, Morris R, Biddle L, Hood B. Investigating the Use of Electronic Well-being Diaries Completed Within a Psychoeducation Program for University Students: Longitudinal Text Analysis Study. Journal of Medical Internet Research 2021;23(4):e25279
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  19. O’Dea B, Boonstra TW, Larsen ME, Nguyen T, Venkatesh S, Christensen H, Boyd RL. The relationship between linguistic expression in blog content and symptoms of depression, anxiety, and suicidal thoughts: A longitudinal study. PLOS ONE 2021;16(5):e0251787
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  20. Dysthe KK, Haavet OR, Røssberg JI, Brandtzaeg PB, Følstad A, Klovning A. Finding Relevant Psychoeducation Content for Adolescents Experiencing Symptoms of Depression: Content Analysis of User-Generated Online Texts. Journal of Medical Internet Research 2021;23(9):e28765
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  21. Savekar A, Tarai S, Singh M. Structural and functional markers of language signify the symptomatic effect of depression: A systematic literature review. European Journal of Applied Linguistics 2023;11(1):190
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  22. Lane JM, Habib D, Curtis B. Linguistic Methodologies to Surveil the Leading Causes of Mortality: Scoping Review of Twitter for Public Health Data. Journal of Medical Internet Research 2023;25:e39484
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  23. Sakib AS, Mukta MSH, Huda FR, Islam AKMN, Islam T, Ali ME. Identifying Insomnia From Social Media Posts: Psycholinguistic Analyses of User Tweets. Journal of Medical Internet Research 2021;23(12):e27613
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  24. Antoniou M, Estival D, Lam-Cassettari C, Li W, Dwyer A, Neto ADA. Predicting Mental Health Status in Remote and Rural Farming Communities: Computational Analysis of Text-Based Counseling. JMIR Formative Research 2022;6(6):e33036
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  25. Liu J, Shi M. What Are the Characteristics of User Texts and Behaviors in Chinese Depression Posts?. International Journal of Environmental Research and Public Health 2022;19(10):6129
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  26. Bioglio L, Pensa RG. Analysis and classification of privacy-sensitive content in social media posts. EPJ Data Science 2022;11(1)
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  28. Bowling J, Montanaro E, Ordonez SG, McCabe S, Farris S, Saint-Cyr N, Glaser W, Cramer RJ, Langhinrichsen-Rohling J, Mennicke A, Al-Yateem N. Coming together in a digital age: Community twitter responses in the wake of a campus shooting. PLOS ONE 2022;17(12):e0279569
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  29. Zhang T, Yang K, Ji S, Ananiadou S. Emotion fusion for mental illness detection from social media: A survey. Information Fusion 2023;92:231
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  30. Bettis AH, Burke TA, Nesi J, Liu RT. Digital Technologies for Emotion-Regulation Assessment and Intervention: A Conceptual Review. Clinical Psychological Science 2022;10(1):3
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  31. Li Z, An Z, Cheng W, Zhou J, Zheng F, Hu B. MHA: a multimodal hierarchical attention model for depression detection in social media. Health Information Science and Systems 2023;11(1)
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  32. Dysthe KK, Røssberg JI, Brandtzaeg PB, Skjuve M, Haavet OR, Følstad A, Klovning A. Analyzing User-Generated Web-Based Posts of Adolescents’ Emotional, Behavioral, and Symptom Responses to Beliefs About Depression: Qualitative Thematic Analysis. Journal of Medical Internet Research 2023;25:e37289
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  33. Hao F, Park E, Chon K. Social Media and Disaster Risk Reduction and Management: How Have Reddit Travel Communities Experienced the COVID-19 Pandemic?. Journal of Hospitality & Tourism Research 2024;48(1):58
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  34. Montag C, Dagum P, Hall BJ, Elhai JD. Do we still need psychological self-report questionnaires in the age of the Internet of Things?. Discover Psychology 2022;2(1)
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  35. Hänsel K, Lin IW, Sobolev M, Muscat W, Yum-Chan S, De Choudhury M, Kane JM, Birnbaum ML. Utilizing Instagram Data to Identify Usage Patterns Associated With Schizophrenia Spectrum Disorders. Frontiers in Psychiatry 2021;12
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  36. Cai Y, Wang H, Ye H, Jin Y, Gao W. Depression detection on online social network with multivariate time series feature of user depressive symptoms. Expert Systems with Applications 2023;217:119538
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  37. Kumar A, Quadir Md A, Christy Jackson J, Iwendi C. Predicting and Curing Depression Using Long Short Term Memory and Global Vector. Computers, Materials & Continua 2023;74(3):5837
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  38. Ragheb W, Aze J, Bringay S, Servajean M. Negatively Correlated Noisy Learners for At-risk User Detection on Social Networks: A Study on Depression, Anorexia, Self-harm and Suicide. IEEE Transactions on Knowledge and Data Engineering 2021;:1
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  39. Giuntini FT, de Moraes KLP, Cazzolato MT, Kirchner LDF, Dos Reis MDJD, Traina AJM, Campbell AT, Ueyama J. Tracing the Emotional Roadmap of Depressive Users on Social Media Through Sequential Pattern Mining. IEEE Access 2021;9:97621
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  40. Santos WRD, de Oliveira RL, Paraboni I. SetembroBR: a social media corpus for depression and anxiety disorder prediction. Language Resources and Evaluation 2024;58(1):273
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  41. Baumeister H, Garatva P, Pryss R, Ropinski T, Montag C. Digitale Phänotypisierung in der Psychologie – ein Quantensprung in der psychologischen Forschung?. Psychologische Rundschau 2023;74(2):89
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  42. Guo Z, Ding N, Zhai M, Zhang Z, Li Z. Leveraging Domain Knowledge to Improve Depression Detection on Chinese Social Media. IEEE Transactions on Computational Social Systems 2023;10(4):1528
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  43. Guo Y, Li Y, Liu D, Xu SX. Measuring service quality based on customer emotion: An explainable AI approach. Decision Support Systems 2024;176:114051
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  44. Obagbuwa IC, Danster S, Chibaya OC. Supervised machine learning models for depression sentiment analysis. Frontiers in Artificial Intelligence 2023;6
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  45. Allen KC, Davis A, Krishnamurti T. Indirect Identification of Perinatal Psychosocial Risks From Natural Language. IEEE Transactions on Affective Computing 2023;14(2):1506
    CrossRef
  46. Farruque N, Goebel R, Sivapalan S, Zaïane OR. Depression symptoms modelling from social media text: an LLM driven semi-supervised learning approach. Language Resources and Evaluation 2024;
    CrossRef

According to Crossref, the following books are citing this article (DOI 10.2196/jmir.9267):

  1. Stankevich M, Smirnov I, Kiselnikova N, Ushakova A. Data Analytics and Management in Data Intensive Domains. 2020. Chapter 12:181
    CrossRef
  2. Marechal C, Mikołajewski D, Tyburek K, Prokopowicz P, Bougueroua L, Ancourt C, Węgrzyn-Wolska K. High-Performance Modelling and Simulation for Big Data Applications. 2019. Chapter 11:307
    CrossRef
  3. Chen LL, Magdy W, Whalley H, Wolters M. Social Informatics. 2020. Chapter 5:58
    CrossRef
  4. Shekerbekova S, Yerekesheva M, Tukenova L, Turganbay K, Kozhamkulova Z, Omarov B. Advanced Informatics for Computing Research. 2021. Chapter 15:161
    CrossRef
  5. Heinz MV, Thomas NX, Nguyen ND, Griffin TZ, Jacobson NC. Comprehensive Clinical Psychology. 2022. :301
    CrossRef
  6. Ingram WM, Khanna R, Weston C. Mental Health Informatics. 2021. Chapter 17:453
    CrossRef
  7. Madera-Torres I, Orozco-del-Castillo MG, Moreno-Cimé SN, Bermejo-Sabbagh C, Cuevas-Cuevas NL. Telematics and Computing. 2023. Chapter 30:473
    CrossRef
  8. Gupta U, Jain V. Emotional AI and Human-AI Interactions in Social Networking. 2024. :15
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  9. Chatterjee M, Modak S, Sarkar D. Cognitive Cardiac Rehabilitation Using IoT and AI Tools. 2023. chapter 4:44
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