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

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/9582, first published .
Increasing Interest of Mass Communication Media and the General Public in the Distribution of Tweets About Mental Disorders: Observational Study

Increasing Interest of Mass Communication Media and the General Public in the Distribution of Tweets About Mental Disorders: Observational Study

Increasing Interest of Mass Communication Media and the General Public in the Distribution of Tweets About Mental Disorders: Observational Study

Journals

  1. Pereira-Sanchez V, Alvarez-Mon M, Asunsolo del Barco A, Alvarez-Mon M, Teo A. Exploring the Extent of the Hikikomori Phenomenon on Twitter: Mixed Methods Study of Western Language Tweets. Journal of Medical Internet Research 2019;21(5):e14167 View
  2. Álvarez-Mon M, Vidal C, Ortuño F. Actualización clínica de la psicosis. Medicine - Programa de Formación Médica Continuada Acreditado 2019;12(86):5023 View
  3. Mavragani A, Ochoa G. Google Trends in Infodemiology and Infoveillance: Methodology Framework. JMIR Public Health and Surveillance 2019;5(2):e13439 View
  4. Alvarez-Mon M, 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 View
  5. Cheng T, Liu L, Woo B. Analyzing Twitter as a Platform for Alzheimer-Related Dementia Awareness: Thematic Analyses of Tweets. JMIR Aging 2018;1(2):e11542 View
  6. Soreni N, Cameron D, Streiner D, Rowa K, McCabe R. Seasonality Patterns of Internet Searches on Mental Health: Exploratory Infodemiology Study. JMIR Mental Health 2019;6(4):e12974 View
  7. Leis A, Ronzano F, Mayer M, Furlong L, Sanz F. Detecting Signs of Depression in Tweets in Spanish: Behavioral and Linguistic Analysis. Journal of Medical Internet Research 2019;21(6):e14199 View
  8. Álvarez-Mon M, Vidal C, Llavero-Valero M, Ortuño F. Actualización clínica de los trastornos depresivos. Medicine - Programa de Formación Médica Continuada Acreditado 2019;12(86):5041 View
  9. Mon M, Sánchez V, de Anta L, Quintero J. Aislamiento social prolongado. Hikikomori: un fenómeno creciente en Occidente. Medicine - Programa de Formación Médica Continuada Acreditado 2019;12(92):5427 View
  10. Roy A, Nikolitch K, McGinn R, Jinah S, Klement W, Kaminsky Z. A machine learning approach predicts future risk to suicidal ideation from social media data. npj Digital Medicine 2020;3(1) View
  11. Viguria I, Alvarez-Mon M, Llavero-Valero M, Asunsolo del Barco A, Ortuño F, Alvarez-Mon M. Eating Disorder Awareness Campaigns: Thematic and Quantitative Analysis Using Twitter. Journal of Medical Internet Research 2020;22(7):e17626 View
  12. Tárraga-Mínguez R, Gómez-Marí I, Sanz-Cervera P. What Motivates Internet Users to Search for Asperger Syndrome and Autism on Google?. International Journal of Environmental Research and Public Health 2020;17(24):9386 View
  13. Álvarez-Mon M, Rodríguez-Quiroga A, de Anta L, Quintero J. Aplicaciones médicas de las redes sociales. Aspectos específicos de la pandemia de la COVID-19. Medicine - Programa de Formación Médica Continuada Acreditado 2020;13(23):1305 View
  14. Alvarez-Mon M, Fernandez-Lazaro C, Llavero-Valero M, Alvarez-Mon M, Mora S, Martinez-Gonzalez M, Bes-Rastrollo M. Mediterranean diet social network impact along 11 years in the major US media outlets: Thematic and Quantitative Analysis using Twitter. (Preprint). JMIR Public Health and Surveillance 2020 View
  15. Lai K, Li D, Peng H, Zhao J, He L. Assessing Suicide Reporting in Top Newspaper Social Media Accounts in China: Content Analysis Study. JMIR Mental Health 2021;8(5):e26654 View
  16. Alvarez-Mon M, Donat-Vargas C, Llavero-Valero M, Gea A, Alvarez-Mon M, Martinez-Gonzalez M, Lopez-del Burgo C. Analysis of Media Outlets on Women's Health: Thematic and Quantitative Analyses Using Twitter. Frontiers in Public Health 2021;9 View
  17. Alvarez-Mon M, de Anta L, Llavero-Valero M, Lahera G, Ortega M, 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 View
  18. Alvarez-Mon M, Llavero-Valero M, Asunsolo del Barco A, Zaragozá C, Ortega M, Lahera G, Quintero J, Alvarez-Mon M. Areas of Interest and Attitudes Toward Antiobesity Drugs: Thematic and Quantitative Analysis Using Twitter. Journal of Medical Internet Research 2021;23(10):e24336 View
  19. Abbasi-Perez A, Alvarez-Mon M, Donat-Vargas C, Ortega M, Monserrat J, Perez-Gomez A, Sanz I, Alvarez-Mon M. Analysis of Tweets Containing Information Related to Rheumatological Diseases on Twitter. International Journal of Environmental Research and Public Health 2021;18(17):9094 View
  20. Pereira-Sanchez V, Alvarez-Mon M, Horinouchi T, Kawagishi R, Tan M, Hooker E, Alvarez-Mon M, Teo A. Examining Tweet Content and Engagement of Users With Tweets About Hikikomori in Japanese: Mixed Methods Study of Social Withdrawal. Journal of Medical Internet Research 2022;24(1):e31175 View
  21. Alvarez-Mon M, Donat-Vargas C, Santoma-Vilaclara J, Anta L, Goena J, Sanchez-Bayona R, Mora F, Ortega M, Lahera G, Rodriguez-Jimenez R, Quintero J, Álvarez-Mon M. Assessment of Antipsychotic Medications on Social Media: Machine Learning Study. Frontiers in Psychiatry 2021;12 View
  22. Alibudbud R. Googling “mental health” after mental health legislation and during the COVID-19 pandemic: an infodemiological study of public interest in mental health in the Philippines. Journal of Mental Health 2022;31(4):568 View
  23. de Anta L, Alvarez-Mon M, Ortega M, 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 View
  24. Alvarez-Mon M, Fernandez-Lazaro C, Ortega M, Vidal C, Molina-Ruiz R, Alvarez-Mon M, Martínez-González M. Analyzing Psychotherapy on Twitter: An 11-Year Analysis of Tweets From Major U.S. Media Outlets. Frontiers in Psychiatry 2022;13 View
  25. Alvarez-Mon M, Fernandez-Lazaro C, Llavero-Valero M, Alvarez-Mon M, Mora S, Martínez-González M, Bes-Rastrollo M. Mediterranean Diet Social Network Impact along 11 Years in the Major US Media Outlets: Thematic and Quantitative Analysis Using Twitter. International Journal of Environmental Research and Public Health 2022;19(2):784 View
  26. Sinha G, Larrison C, Brooks I. Twitter sentiments and mental health services in the United States. Social Work in Mental Health 2024;22(1):91 View
  27. Alvarez-Mon M, Pereira-Sanchez V, Hooker E, Sanchez F, Alvarez-Mon M, Teo A. Content and User Engagement of Health-Related Behavior Tweets Posted by Mass Media Outlets From Spain and the United States Early in the COVID-19 Pandemic: Observational Infodemiology Study. JMIR Infodemiology 2023;3:e43685 View
  28. Bello H, Palomar-Ciria N, Lozano C, Gutiérrez-Alonso C, Baca-García E. Examining the relationship between COVID-19 and suicide in media coverage through Natural Language Processing analysis. The European Journal of Psychiatry 2024;38(1):100227 View
  29. Carabot F, Fraile-Martínez O, Donat-Vargas C, Santoma J, Garcia-Montero C, Pinto da Costa M, Molina-Ruiz R, Ortega M, Alvarez-Mon M, Alvarez-Mon M. Understanding Public Perceptions and Discussions on Opioids Through Twitter: Cross-Sectional Infodemiology Study. Journal of Medical Internet Research 2023;25:e50013 View
  30. Esmaeilzadeh P. Privacy Concerns About Sharing General and Specific Health Information on Twitter: Quantitative Study. JMIR Formative Research 2024;8:e45573 View
  31. Correia Lopes F, Pinto da Costa M, Fernandez-Lazaro C, Lara-Abelenda F, Pereira-Sanchez V, Teo A, Alvarez-Mon M. Analysis of the hikikomori phenomenon – an international infodemiology study of Twitter data in Portuguese. BMC Public Health 2024;24(1) View
  32. Domingo-Espiñeira J, Fraile-Martínez O, Garcia-Montero C, Montero M, Varaona A, Lara-Abelenda F, Ortega M, Alvarez-Mon M, Alvarez-Mon M. Navigating the Digital Neurolandscape: Analyzing the Social Perception of and Sentiments Regarding Neurological Disorders through Topic Modeling and Unsupervised Research Using Twitter. Information 2024;15(3):152 View
  33. Castillo-Toledo C, Fraile-Martínez O, Donat-Vargas C, Lara-Abelenda F, Ortega M, Garcia-Montero C, Mora F, Alvarez-Mon M, Quintero J, Alvarez-Mon M. Insights from the Twittersphere: a cross-sectional study of public perceptions, usage patterns, and geographical differences of tweets discussing cocaine. Frontiers in Psychiatry 2024;15 View
  34. Ng Q, Lim Y, Ong C, New S, Fam J, Liew T. Hype or hope? Ketamine for the treatment of depression: results from the application of deep learning to Twitter posts from 2010 to 2023. Frontiers in Psychiatry 2024;15 View
  35. Castillo-Toledo C, Fernandez-Lazaro C, Lara-Abelenda F, Molina-Ruiz R, Ortega M, Mora F, Alvarez-Mon M, Quintero J, Alvarez-Mon M. Regional insights on tobacco-related tweets: unveiling user opinions and usage patterns. Frontiers in Public Health 2024;12 View
  36. Cho H, Kim K, Kim J, Youn B. Twitter Discussions on #digitaldementia: Content and Sentiment Analysis. Journal of Medical Internet Research 2024;26:e59546 View
  37. Valades M, Montero-Torres M, Lara-Abelenda F, Carabot F, Ortega M, Álvarez-Mon M, Alvarez-Mon M. Understanding public perceptions and discussions on diseases involving chronic pain through social media: cross-sectional infodemiology study. BMC Musculoskeletal Disorders 2024;25(1) View
  38. de Anta L, Alvarez-Mon M, Pereira-Sanchez V, Donat-Vargas C, Lara-Abelenda F, Arrieta M, Montero-Torres M, García-Montero C, Fraile-Martínez Ó, Mora F, Ortega M, Alvarez-Mon M, Quintero J. Assessment of beliefs and attitudes towards benzodiazepines using machine learning based on social media posts: an observational study. BMC Psychiatry 2024;24(1) View