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Citing this Article

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Published on 18.10.17 in Vol 4, No 4 (2017): Oct-Dec

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

Works citing "#MyDepressionLooksLike: Examining Public Discourse About Depression on Twitter"

E Megan Lachmar, Andrea K Wittenborn, Katherine W Bogen, Heather L McCauley

JMIR Ment Health 2017 (Oct 18); 4(4):e43 

According to Crossref, the following articles are citing this article (DOI 10.2196/mental.8141):

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

  1. Alvarez-Mon MA, Llavero-Valero M, Sánchez-Bayona R, Pereira-Sanchez V, Vallejo-Valdivielso M, Monserrat J, Lahera G, Asunsolo del Barco A, Alvarez-Mon M. Areas of Interest and Stigmatic Attitudes of the General Public in Five Relevant Medical Conditions: Thematic and Quantitative Analysis Using Twitter. Journal of Medical Internet Research 2019;21(5):e14110
    CrossRef
  2. Kelleher E, Moreno M, Wilt MP. Recruitment of Participants and Delivery of Online Mental Health Resources for Depressed Individuals Using Tumblr: Pilot Randomized Control Trial. JMIR Research Protocols 2018;7(4):e95
    CrossRef
  3. Brandt HM, Turner-McGrievy G, Friedman DB, Gentile D, Schrock C, Thomas T, West D. Examining the Role of Twitter in Response and Recovery During and After Historic Flooding in South Carolina. Journal of Public Health Management and Practice 2019;25(5):E6
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  4. Szlyk H, Deng J, Xu C, Krauss MJ, Cavazos‐Rehg PA. Leveraging social media to explore the barriers to treatment among individuals with depressive symptoms. Depression and Anxiety 2020;37(5):458
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  5. Khasawneh A, Chalil Madathil K, Dixon E, Wiśniewski P, Zinzow H, Roth R. Examining the Self-Harm and Suicide Contagion Effects of the Blue Whale Challenge on YouTube and Twitter: Qualitative Study. JMIR Mental Health 2020;7(6):e15973
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  6. Schlichthorst M, King K, Turnure J, Sukunesan S, Phelps A, Pirkis J. Influencing the Conversation About Masculinity and Suicide: Evaluation of the Man Up Multimedia Campaign Using Twitter Data. JMIR Mental Health 2018;5(1):e14
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  7. Harlow AF, Willis SK, Smith ML, Rothman EF. Bystander Prevention for Sexual Violence: #HowIWillChange and Gaps in Twitter Discourse. Journal of Interpersonal Violence 2021;36(11-12):NP5753
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  8. Giuntini FT, Cazzolato MT, dos Reis MDJD, Campbell AT, Traina AJM, Ueyama J. A review on recognizing depression in social networks: challenges and opportunities. Journal of Ambient Intelligence and Humanized Computing 2020;11(11):4713
    CrossRef
  9. Pan J, Liu B, Kreps GL. A content analysis of depression-related discourses on Sina Weibo: attribution, efficacy, and information sources. BMC Public Health 2018;18(1)
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  10. Garcia-Rudolph A, Laxe S, Saurí J, Bernabeu Guitart M. Stroke Survivors on Twitter: Sentiment and Topic Analysis From a Gender Perspective. Journal of Medical Internet Research 2019;21(8):e14077
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  11. Michalak EE, Morton E, Barnes SJ, Hole R, Murray G. Supporting Self-Management in Bipolar Disorder: Mixed-Methods Knowledge Translation Study. JMIR Mental Health 2019;6(4):e13493
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  12. Logghe HJ, Selby LV, Boeck MA, Stamp NL, Chuen J, Jones C. The academic tweet: Twitter as a tool to advance academic surgery. Journal of Surgical Research 2018;226:viii
    CrossRef
  13. McCauley HL, Bonomi AE, Maas MK, Bogen KW, O'Malley TL. #MaybeHeDoesntHitYou: Social Media Underscore the Realities of Intimate Partner Violence. Journal of Women's Health 2018;27(7):885
    CrossRef
  14. Fonseka TM, Bhat V, Kennedy SH. The utility of artificial intelligence in suicide risk prediction and the management of suicidal behaviors. Australian & New Zealand Journal of Psychiatry 2019;53(10):954
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  15. Reinisch A, Schröder SR, Ulrich F, Padberg W, Liese J. Antibiotic-treated acute appendicitis—reception in social media. Langenbeck's Archives of Surgery 2019;404(3):343
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  16. DeJohn AD, Schulz EE, Pearson AL, Lachmar EM, Wittenborn AK. Identifying and Understanding Communities Using Twitter to Connect About Depression: Cross-Sectional Study. JMIR Mental Health 2018;5(4):e61
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  17. Makita M, Mas-Bleda A, Morris S, Thelwall M. Mental Health Discourses on Twitter during Mental Health Awareness Week. Issues in Mental Health Nursing 2021;42(5):437
    CrossRef
  18. Doan S, Yang EW, Tilak SS, Li PW, Zisook DS, Torii M. Extracting health-related causality from twitter messages using natural language processing. BMC Medical Informatics and Decision Making 2019;19(S3)
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  19. . Infodemiology and Infoveillance: Scoping Review. Journal of Medical Internet Research 2020;22(4):e16206
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  20. Delanys S, Benamara F, Moriceau V, Olivier F, Mothe J. Psychiatry on Twitter: Content Analysis of the Use of Psychiatric Terms in French. JMIR Formative Research 2022;6(2):e18539
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  21. Skaik R, Inkpen D. Using Social Media for Mental Health Surveillance. ACM Computing Surveys 2021;53(6):1
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  22. Sipocz D, Freeman JD, Elton J, Bowers BJ. “A Toxic Trend?”: Generational Conflict and Connectivity in Twitter Discourse Under the #BoomerRemover Hashtag. The Gerontologist 2021;61(2):166
    CrossRef
  23. Coll-Florit M, Climent S, Sanfilippo M, Hernández-Encuentra E. Metaphors of Depression. Studying First Person Accounts of Life with Depression Published in Blogs. Metaphor and Symbol 2021;36(1):1
    CrossRef
  24. Nicholas J, Onie S, Larsen ME. Ethics and Privacy in Social Media Research for Mental Health. Current Psychiatry Reports 2020;22(12)
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  25. Németh R, Sik D, Katona E. The asymmetries of the biopsychosocial model of depression in lay discourses - Topic modelling online depression forums. SSM - Population Health 2021;14:100785
    CrossRef
  26. Khasawneh A, Chalil Madathil K, Zinzow H, Rosopa P, Natarajan G, Achuthan K, Narasimhan M. Factors Contributing to Adolescents’ and Young Adults’ Participation in Web-Based Challenges: Survey Study. JMIR Pediatrics and Parenting 2021;4(1):e24988
    CrossRef
  27. Alvarez-Mon MA, de Anta L, Llavero-Valero M, Lahera G, Ortega MA, Soutullo C, Quintero J, Asunsolo del Barco A, Alvarez-Mon M. Areas of Interest and Attitudes towards the Pharmacological Treatment of Attention Deficit Hyperactivity Disorder: Thematic and Quantitative Analysis Using Twitter. Journal of Clinical Medicine 2021;10(12):2668
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  28. Cohrdes C, Yenikent S, Wu J, Ghanem B, Franco-Salvador M, Vogelgesang F. Indications of Depressive Symptoms During the COVID-19 Pandemic in Germany: Comparison of National Survey and Twitter Data. JMIR Mental Health 2021;8(6):e27140
    CrossRef
  29. Chilman N, Morant N, Lloyd-Evans B, Wackett J, Johnson S. Twitter Users’ Views on Mental Health Crisis Resolution Team Care Compared With Stakeholder Interviews and Focus Groups: Qualitative Analysis. JMIR Mental Health 2021;8(6):e25742
    CrossRef
  30. Gutierrez E, Karwowski W, Fiok K, Davahli MR, Liciaga T, Ahram T. Analysis of Human Behavior by Mining Textual Data: Current Research Topics and Analytical Techniques. Symmetry 2021;13(7):1276
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  31. Ricard BJ, Hassanpour S. Deep Learning for Identification of Alcohol-Related Content on Social Media (Reddit and Twitter): Exploratory Analysis of Alcohol-Related Outcomes. Journal of Medical Internet Research 2021;23(9):e27314
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  32. Nawaz FA, Riaz MMA, Tsagkaris C, Faisal UH, Klager E, Kletecka-Pulker M, Kimberger O, Willschke H, Khan N, Sultan MA, Atanasov AG. Impact of #PsychTwitter in promoting global psychiatry: A hashtag analysis study. Frontiers in Public Health 2023;11
    CrossRef
  33. Németh R, Máté F, Katona E, Rakovics M, Sik D. Bio, psycho, or social: supervised machine learning to classify discursive framing of depression in online health communities. Quality & Quantity 2022;56(6):3933
    CrossRef
  34. Sik D, Németh R, Katona E. Topic modelling online depression forums: beyond narratives of self-objectification and self-blaming. Journal of Mental Health 2023;32(2):386
    CrossRef
  35. Stupinski AM, Alshaabi T, Arnold MV, Adams JL, Minot JR, Price M, Dodds PS, Danforth CM. Quantifying Changes in the Language Used Around Mental Health on Twitter Over 10 Years: Observational Study. JMIR Mental Health 2022;9(3):e33685
    CrossRef
  36. Akhther N, Sopory P. Seeking and Sharing Mental Health Information on Social Media During COVID-19: Role of Depression and Anxiety, Peer Support, and Health Benefits. Journal of Technology in Behavioral Science 2022;7(2):211
    CrossRef
  37. Freeman JD, Elton J, Sipocz D. ‘Defined by the #CoronavirusOutbreak’: characterizing Gen Z in Twitter discourse surrounding COVID-19. Journal of Youth Studies 2023;26(9):1130
    CrossRef
  38. Culp F, Wu Y, Wu D, Ren Y, Raynor P, Hung P, Qiao S, Li X, Eichelberger K. Understanding Alcohol Use Discourse and Stigma Patterns in Perinatal Care on Twitter. Healthcare 2022;10(12):2375
    CrossRef
  39. 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
    CrossRef
  40. Bacsu JR, O'Connell ME, Cammer A, Ahmadi S, Berger C, Azizi M, Gowda-Sookochoff R, Grewal KS, Green S, Knight S, Spiteri RJ. Examining the Impact of COVID-19 on People With Dementia From the Perspective of Family and Friends: Thematic Analysis of Tweets. JMIR Aging 2022;5(2):e38363
    CrossRef
  41. de Anta L, Alvarez-Mon MA, Ortega MA, Salazar C, Donat-Vargas C, Santoma-Vilaclara J, Martin-Martinez M, Lahera G, Gutierrez-Rojas L, Rodriguez-Jimenez R, Quintero J, Alvarez-Mon M. Areas of Interest and Social Consideration of Antidepressants on English Tweets: A Natural Language Processing Classification Study. Journal of Personalized Medicine 2022;12(2):155
    CrossRef
  42. Bizzotto N, Morlino S, Schulz PJ. Misinformation in Italian Online Mental Health Communities During the COVID-19 Pandemic: Protocol for a Content Analysis Study. JMIR Research Protocols 2022;11(5):e35347
    CrossRef
  43. 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
    CrossRef
  44. Correa-Urquiza Vidal M, Pié Balaguer A, Coll-Florit M, Hernández i Encuentra E, Climent S. Orgullo loco y metáforas para una disidencia: un análisis lingüístico y simbólico. Salud Colectiva 2020;16:e2886
    CrossRef
  45. Li J, Tang L, Pu Y. My Story of Depression: A Content Analysis of Autobiographic Videos on Douyin. Health Communication 2024;39(5):906
    CrossRef
  46. Dhelim S, Chen L, Das SK, 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
    CrossRef
  47. Gu L, Ding H. A bibliometric analysis of media coverage of mental disorders between 2002 and 2022. Social Psychiatry and Psychiatric Epidemiology 2023;58(11):1719
    CrossRef
  48. Zhu J, Li Z, Zhang X, Zhang Z, Hu B. Public Attitudes Toward Anxiety Disorder on Sina Weibo: Content Analysis. Journal of Medical Internet Research 2023;25:e45777
    CrossRef
  49. Aruah DE, Henshaw Y, Walsh-Childers K. Tweets That Matter: Exploring the Solutions to Maternal Mortality in the United States Discussed by Advocacy Organizations on Twitter. International Journal of Environmental Research and Public Health 2023;20(9):5617
    CrossRef
  50. Malloch YZ, Zhang J, Qian S. Effects of social comparison direction, comparison distance, and message framing on health behavioral intention in online support groups. Cyberpsychology: Journal of Psychosocial Research on Cyberspace 2023;17(3)
    CrossRef
  51. Carabot F, Donat-Vargas C, Santoma-Vilaclara J, Ortega MA, García-Montero C, Fraile-Martínez O, Zaragoza C, Monserrat J, Alvarez-Mon M, Alvarez-Mon MA. Exploring Perceptions About Paracetamol, Tramadol, and Codeine on Twitter Using Machine Learning: Quantitative and Qualitative Observational Study. Journal of Medical Internet Research 2023;25:e45660
    CrossRef
  52. Németh R, Sik D, Zaboretzky B, Katona E. Depression in times of a pandemic – the impact of COVID-19 on the lay discourses of e-mental health communities. Information, Communication & Society 2024;27(3):538
    CrossRef
  53. Carabot F, Fraile-Martínez O, Donat-Vargas C, Santoma J, Garcia-Montero C, Pinto da Costa M, Molina-Ruiz RM, Ortega MA, Alvarez-Mon M, Alvarez-Mon MA. Understanding Public Perceptions and Discussions on Opioids Through Twitter: Cross-Sectional Infodemiology Study. Journal of Medical Internet Research 2023;25:e50013
    CrossRef
  54. Chin H, Song H, Baek G, Shin M, Jung C, Cha M, Choi J, Cha C. The Potential of Chatbots for Emotional Support and Promoting Mental Well-Being in Different Cultures: Mixed Methods Study. Journal of Medical Internet Research 2023;25:e51712
    CrossRef
  55. Talbot A, Ford T, Ryan S, Mahtani KR, Albury C. #TreatmentResistantDepression: A qualitative content analysis of Tweets about difficult‐to‐treat depression. Health Expectations 2023;26(5):1986
    CrossRef
  56. DeJohn AD, Widener MJ, Mihailidis A. Who uses technology to socialize? Evidence from older Canadian adults. Discover Social Science and Health 2023;3(1)
    CrossRef
  57. Tambling RR, D’Aniello - Heyda C, Hynes KC. Manifestations of Depression on Social Media: a Content Analysis of Twitter Posts. Journal of Technology in Behavioral Science 2023;
    CrossRef
  58. Sik D, Rakovics M, Buda J, Németh R. The impact of depression forums on illness narratives: a comprehensive NLP analysis of socialization in e-mental health communities. Journal of Computational Social Science 2023;6(2):781
    CrossRef
  59. Aldkheel A, Zhou L. Depression Detection on Social Media: A Classification Framework and Research Challenges and Opportunities. Journal of Healthcare Informatics Research 2024;8(1):88
    CrossRef
  60. Chart-Pascual JP, Montero-Torres M, Ortega MA, Mar-Barrutia L, Zorrilla Martinez I, Alvarez-Mon M, Gonzalez-Pinto A, Alvarez-Mon MA. Areas of interest and sentiment analysis towards second generation antipsychotics, lithium and mood stabilizing anticonvulsants: Unsupervised analysis using Twitter. Journal of Affective Disorders 2024;351:649
    CrossRef
  61. Russo R, Seedall RB, Aller TB, Clark JK. #ThisIsWhatAnxietyFeelsLike: Twitter Users’ Narratives of the Interpersonal Effects of Anxiety. Contemporary Family Therapy 2024;
    CrossRef
  62. 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
    CrossRef
  63. Issaka B, Aidoo EAK, Wood SF, Mohammed F. “Anxiety is not cute” analysis of twitter users’ discourses on romanticizing mental illness. BMC Psychiatry 2024;24(1)
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  64. . Quoting and well-being: researching social media posts of two mental health campaigns in Hong Kong. Journal of Multilingual and Multicultural Development 2024;:1
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According to Crossref, the following books are citing this article (DOI 10.2196/mental.8141):

  1. Bollen J, ten Thij M, Lorenzo-Luaces L, Rutter LA. Early Detection of Mental Health Disorders by Social Media Monitoring. 2022. Chapter 12:265
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  2. . Women’s Activism Online and the Global Struggle for Social Change. 2023. Chapter 7:133
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  3. Thakur N, Cho H, Cheng H, Lee H. HCI International 2023 – Late Breaking Papers. 2023. Chapter 27:367
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