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

Medicine 2.0'13 London (Full Paper of Conference Presentation) (30)

Published on in Vol 15, No 10 (2013): October

Activities on Facebook Reveal the Depressive State of Users

Activities on Facebook Reveal the Depressive State of Users

Activities on Facebook Reveal the Depressive State of Users

Authors of this article:

Sungkyu Park1 ;   Sang Won Lee2 ;   Jinah Kwak3 ;   Meeyoung Cha3 ;   Bumseok Jeong2
Article Authors Cited by (95) Tweetations (19) Metrics

Journals

  1. Park M, Chung M. Mediating Effects of Interpersonal Problems in the Relationship between Social Network Service Use Tendency and Depression among University Students. Journal of Korean Academy of Community Health Nursing 2019;30(1):38 View
  2. Grande D, Luna Marti X, Feuerstein-Simon R, Merchant R, Asch D, Lewson A, Cannuscio C. Health Policy and Privacy Challenges Associated With Digital Technology. JAMA Network Open 2020;3(7):e208285 View
  3. Rohani D, Faurholt-Jepsen M, Kessing L, Bardram J. Correlations Between Objective Behavioral Features Collected From Mobile and Wearable Devices and Depressive Mood Symptoms in Patients With Affective Disorders: Systematic Review. JMIR mHealth and uHealth 2018;6(8):e165 View
  4. Frost R, Rickwood D. A systematic review of the mental health outcomes associated with Facebook use. Computers in Human Behavior 2017;76:576 View
  5. Peng Z, Hu Q, Dang J. Multi-kernel SVM based depression recognition using social media data. International Journal of Machine Learning and Cybernetics 2019;10(1):43 View
  6. Naja W, Kansoun A, Haddad R. Prevalence of Depression in Medical Students at the Lebanese University and Exploring its Correlation With Facebook Relevance: A Questionnaire Study. JMIR Research Protocols 2016;5(2):e96 View
  7. Seabrook E, Kern M, Rickard N. Social Networking Sites, Depression, and Anxiety: A Systematic Review. JMIR Mental Health 2016;3(4):e50 View
  8. Coşkun M, Ozturan M. #europehappinessmap: A Framework for Multi-Lingual Sentiment Analysis via Social Media Big Data (A Twitter Case Study). Information 2018;9(5):102 View
  9. Ophir Y, Asterhan C, Schwarz B. The digital footprints of adolescent depression, social rejection and victimization of bullying on Facebook. Computers in Human Behavior 2019;91:62 View
  10. Ko M, Yeo J, Lee J, Lee U, Jang Y, Cristani M. What Makes Sports Fans Interactive? Identifying Factors Affecting Chat Interactions in Online Sports Viewing. PLOS ONE 2016;11(2):e0148377 View
  11. Gao J, Zhang Y, Zhou T. Computational socioeconomics. Physics Reports 2019;817:1 View
  12. Cavazos-Rehg P, Krauss M, Sowles S, Connolly S, Rosas C, Bharadwaj M, Grucza R, Bierut L. An Analysis of Depression, Self-Harm, and Suicidal Ideation Content on Tumblr. Crisis 2017;38(1):44 View
  13. Zhang A, Rau P. A Review and Reappraisal of Social Media Misuse: Measurements, Consequences, and Predictors. International Journal of Human–Computer Interaction 2021;37(1):1 View
  14. Hussain J, Satti F, Afzal M, Khan W, Bilal H, Ansaar M, Ahmad H, Hur T, Bang J, Kim J, Park G, Seung H, Lee S. Exploring the dominant features of social media for depression detection. Journal of Information Science 2020;46(6):739 View
  15. Yoshida S, Hijikata Y. Envy Sensitivity on Twitter and Facebook Among Japanese Young Adults. International Journal of Cyber Behavior, Psychology and Learning 2017;7(1):18 View
  16. Vahedi Z, Zannella L. The association between self-reported depressive symptoms and the use of social networking sites (SNS): A meta-analysis. Current Psychology 2021;40(5):2174 View
  17. Pantic I. Online Social Networking and Mental Health. Cyberpsychology, Behavior, and Social Networking 2014;17(10):652 View
  18. Smith R, Crutchley P, Schwartz H, Ungar L, Shofer F, Padrez K, Merchant R. Variations in Facebook Posting Patterns Across Validated Patient Health Conditions: A Prospective Cohort Study. Journal of Medical Internet Research 2017;19(1):e7 View
  19. Fatima I, Mukhtar H, Ahmad H, Rajpoot K. Analysis of user-generated content from online social communities to characterise and predict depression degree. Journal of Information Science 2018;44(5):683 View
  20. Chancellor S, De Choudhury M. Methods in predictive techniques for mental health status on social media: a critical review. npj Digital Medicine 2020;3(1) View
  21. Patel R, Chang T, Greysen S, Chopra V. Social Media Use in Chronic Disease: A Systematic Review and Novel Taxonomy. The American Journal of Medicine 2015;128(12):1335 View
  22. Byaruhanga J, Tzelepis F, Paul C, Wiggers J, Byrnes E, Lecathelinais C. Cost Per Participant Recruited From Rural and Remote Areas Into a Smoking Cessation Trial Via Online or Traditional Strategies: Observational Study. Journal of Medical Internet Research 2019;21(11):e14911 View
  23. Tosun L, Kaşdarma E. Passive Facebook Use and Depression. Journal of Media Psychology 2020;32(4):165 View
  24. Cheng P, Ramos R, Bitsch J, Jonas S, Ix T, See P, Wehrle K. Psychologist in a Pocket: Lexicon Development and Content Validation of a Mobile-Based App for Depression Screening. JMIR mHealth and uHealth 2016;4(3):e88 View
  25. Wee J, Jang S, Lee J, Jang W. The influence of depression and personality on social networking. Computers in Human Behavior 2017;74:45 View
  26. Xu X, Litchman M, Gee P, Whatcott W, Chacon L, Holmes J, Srinivasan S. Predicting Prediabetes Through Facebook Postings: Protocol for a Mixed-Methods Study. JMIR Research Protocols 2018;7(12):e10720 View
  27. Gwynette M, Morriss D, Warren N, Truelove J, Warthen J, Ross C, Mood G, Snook C, Borckardt J. Social Skills Training for Adolescents With Autism Spectrum Disorder Using Facebook (Project Rex Connect): A Survey Study. JMIR Mental Health 2017;4(1):e4 View
  28. Giuntini F, Cazzolato M, dos Reis M, Campbell A, Traina A, Ueyama J. A review on recognizing depression in social networks: challenges and opportunities. Journal of Ambient Intelligence and Humanized Computing 2020;11(11):4713 View
  29. Dogrucu A, Perucic A, Isaro A, Ball D, Toto E, Rundensteiner E, Agu E, Davis-Martin R, Boudreaux E. Moodable: On feasibility of instantaneous depression assessment using machine learning on voice samples with retrospectively harvested smartphone and social media data. Smart Health 2020;17:100118 View
  30. Asch D, Rader D, Merchant R. Mining the social mediome. Trends in Molecular Medicine 2015;21(9):528 View
  31. Padrez K, Ungar L, Schwartz H, Smith R, Hill S, Antanavicius T, Brown D, Crutchley P, Asch D, Merchant R. Linking social media and medical record data: a study of adults presenting to an academic, urban emergency department. BMJ Quality & Safety 2016;25(6):414 View
  32. Parikh S, Huniewicz P. E-health. Current Opinion in Psychiatry 2015;28(1):13 View
  33. Settanni M, Marengo D. Sharing feelings online: studying emotional well-being via automated text analysis of Facebook posts. Frontiers in Psychology 2015;6 View
  34. Webb C, Rosso I, Rauch S. Internet-Based Cognitive-Behavioral Therapy for Depression: Current Progress and Future Directions. Harvard Review of Psychiatry 2017;25(3):114 View
  35. Baker D, Algorta G. The Relationship Between Online Social Networking and Depression: A Systematic Review of Quantitative Studies. Cyberpsychology, Behavior, and Social Networking 2016;19(11):638 View
  36. Zhang R, Fu J. Linking Network Characteristics of Online Social Networks to Individual Health: A Systematic Review of Literature. Health Communication 2021;36(12):1549 View
  37. Guha M, Seale L. “Reading maketh a full man”. Journal of Mental Health 2015;24(5):257 View
  38. Fisher C, Appelbaum P. Beyond Googling: The Ethics of Using Patients' Electronic Footprints in Psychiatric Practice. Harvard Review of Psychiatry 2017;25(4):170 View
  39. Pitman A, Osborn D, King M. The use of internet-mediated cross-sectional studies in mental health research. BJPsych Advances 2015;21(3):175 View
  40. Dao B, Nguyen T, Venkatesh S, Phung D. Latent sentiment topic modelling and nonparametric discovery of online mental health-related communities. International Journal of Data Science and Analytics 2017;4(3):209 View
  41. Chancellor S, Baumer E, De Choudhury M. Who is the "Human" in Human-Centered Machine Learning. Proceedings of the ACM on Human-Computer Interaction 2019;3(CSCW):1 View
  42. Wongkoblap A, Vadillo M, Curcin V. Researching Mental Health Disorders in the Era of Social Media: Systematic Review. Journal of Medical Internet Research 2017;19(6):e228 View
  43. Lim M, Wright C, Carrotte E, Pedrana A. Reach, engagement, and effectiveness: a systematic review of evaluation methodologies used in health promotion via social networking sites. Health Promotion Journal of Australia 2016;27(3):187 View
  44. Scherr S, Brunet A. Differential Influences of Depression and Personality Traits on the Use of Facebook. Social Media + Society 2017;3(1) View
  45. Zhang R. The stress-buffering effect of self-disclosure on Facebook: An examination of stressful life events, social support, and mental health among college students. Computers in Human Behavior 2017;75:527 View
  46. Fleming M. Considerations for the ethical implementation of psychological assessment through social media via machine learning. Ethics & Behavior 2021;31(3):181 View
  47. Kelly D, Spaderna M, Hodzic V, Nair S, Kitchen C, Werkheiser A, Powell M, Liu F, Coppersmith G, Chen S, Resnik P. Blinded Clinical Ratings of Social Media Data are Correlated with In-Person Clinical Ratings in Participants Diagnosed with Either Depression, Schizophrenia, or Healthy Controls. Psychiatry Research 2020;294:113496 View
  48. Rehman A, Naz S, Razzak I. Leveraging big data analytics in healthcare enhancement: trends, challenges and opportunities. Multimedia Systems 2022;28(4):1339 View
  49. Sadagheyani H, Tatari F. Investigating the role of social media on mental health. Mental Health and Social Inclusion 2021;25(1):41 View
  50. Stevanovic M, Tuhkanen S, Järvensivu M, Koskinen E, Savander E, Valkia K, Tay D. Physiological responses to proposals during dyadic decision-making conversations. PLOS ONE 2021;16(1):e0244929 View
  51. Kim J, Uddin Z, Lee Y, Nasri F, Gill H, Subramanieapillai M, Lee R, Udovica A, Phan L, Lui L, Iacobucci M, Mansur R, Rosenblat J, McIntyre R. A Systematic review of the validity of screening depression through Facebook, Twitter, Instagram, and Snapchat. Journal of Affective Disorders 2021;286:360 View
  52. Dysthe K, Haavet O, Røssberg J, Brandtzaeg P, 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 View
  53. Limniou M, Ascroft Y, McLean S. Differences between Facebook and Instagram Usage in Regard to Problematic Use and Well-Being. Journal of Technology in Behavioral Science 2022;7(2):141 View
  54. Santos W, de Oliveira R, Paraboni I. SetembroBR: a social media corpus for depression and anxiety disorder prediction. Language Resources and Evaluation 2024;58(1):273 View
  55. Dysthe K, Røssberg J, Brandtzaeg P, Skjuve M, Haavet O, 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 View
  56. Hemphill T, Banerjee S. Facebook and self-regulation: Efficacious proposals – Or ‘smoke-and-mirrors’?. Technology in Society 2021;67:101797 View
  57. Ulvi O, Karamehic-Muratovic A, Baghbanzadeh M, Bashir A, Smith J, Haque U. Social Media Use and Mental Health: A Global Analysis. Epidemiologia 2022;3(1):11 View
  58. Yue C, Ware S, Morillo R, Lu J, Shang C, Bi J, Kamath J, Russell A, Bamis A, Wang B. Automatic depression prediction using Internet traffic characteristics on smartphones. Smart Health 2020;18:100137 View
  59. Mandryk R, Birk M, Vedress S, Wiley K, Reid E, Berger P, Frommel J. Remote Assessment of Depression Using Digital Biomarkers From Cognitive Tasks. Frontiers in Psychology 2021;12 View
  60. Ortega-Mendoza R, Hernández-Farías D, Montes-y-Gómez M, Villaseñor-Pineda L. Revealing traces of depression through personal statements analysis in social media. Artificial Intelligence in Medicine 2022;123:102202 View
  61. Taghvaei N, Masoumi B, Keyvanpour M. Analytical framework for mental health feature extraction methods in social networks. Intelligent Decision Technologies 2021;15(3):343 View
  62. Dhelim S, Chen L, Das S, Ning H, Nugent C, Leavey G, Pesch D, Bantry-White E, Burns D. Detecting Mental Distresses Using Social Behavior Analysis in the Context of COVID-19: A Survey. ACM Computing Surveys 2023;55(14s):1 View
  63. Hilty D, Stubbe D, McKean A, Hoffman P, Zalpuri I, Myint M, Joshi S, Pakyurek M, Li S. A scoping review of social media in child, adolescents and young adults: research findings in depression, anxiety and other clinical challenges. BJPsych Open 2023;9(5) View
  64. Stangl F, Riedl R, Kiemeswenger R, Montag C. Negative psychological and physiological effects of social networking site use: The example of Facebook. Frontiers in Psychology 2023;14 View
  65. Khare J, Kalra S, Jindal S. Sociocrinology: Impact of Social Media on Endocrine Health – A Review. Indian Journal of Endocrinology and Metabolism 2023;27(6):480 View
  66. Maruf A, Khanam F, Haque M, Jiyad Z, Mridha M, Aung Z. Challenges and Opportunities of Text-Based Emotion Detection: A Survey. IEEE Access 2024;12:18416 View
  67. Ambrose A. The Virtual Blues: Facebook and Depression in Young Adults. American Journal of Psychiatry Residents' Journal 2016;11(12):3 View
  68. Aldridge Z, McDermott H, Thorne N, Arcelus J, Witcomb G. Social Media Creations of Community and Gender Minority Stress in Transgender and Gender-Diverse Adults. Social Sciences 2024;13(9):483 View
  69. Xiao Y, Yang Y, Xu H, Li S. Empirical insights into the interaction effects of groups at high risk of depression on online social platforms with NLP-based sentiment analysis. Data and Information Management 2024;8(4):100080 View
  70. Benetoli A, Chen T, Aslani P. Consumer perceptions of using social media for health purposes: Benefits and drawbacks. Health Informatics Journal 2019;25(4):1661 View

Books/Policy Documents

  1. Ebert D, Harrer M, Apolinário-Hagen J, Baumeister H. Frontiers in Psychiatry. View
  2. Moreno M, Pumper M. The Wiley Handbook of Psychology, Technology, and Society. View
  3. Su Y, Zheng H, Liu X, Zhu T. Human Centered Computing. View
  4. Yusof N, Lin C, He Y. Encyclopedia of Social Network Analysis and Mining. View
  5. Orta I, Örücü M. Intimacy and Developing Personal Relationships in the Virtual World. View
  6. Yusof N, Lin C, He Y. Encyclopedia of Social Network Analysis and Mining. View
  7. Hosseini-Saravani S, Besharati S, Calvo H, Gelbukh A. Advances in Computational Intelligence. View
  8. Witherspoon T, Auriemma A, Perrelli K. Successes and Setbacks of Social Media. View
  9. Orta I, Örücü M. Research Anthology on Usage, Identity, and Impact of Social Media on Society and Culture. View
  10. Heinz M, Thomas N, Nguyen N, Griffin T, Jacobson N. Comprehensive Clinical Psychology. View
  11. Orta I, Örücü M. Research Anthology on Combating Cyber-Aggression and Online Negativity. View
  12. Dokuka S, Sivak E, Smirnov I. Network Science. View
  13. Wongkoblap A, Vadillo M, Curcin V. Mental Health in a Digital World. View
  14. Safa R, Edalatpanah S, Sorourkhah A. Deep Learning in Personalized Healthcare and Decision Support. View