Published on in Vol 2, No 1 (2016): Jan-Jun

The Measles Vaccination Narrative in Twitter: A Quantitative Analysis

The Measles Vaccination Narrative in Twitter: A Quantitative Analysis

The Measles Vaccination Narrative in Twitter: A Quantitative Analysis

Journals

  1. Marcon A, Klostermann P, Caulfield T. Chiropractic and Spinal Manipulation Therapy on Twitter: Case Study Examining the Presence of Critiques and Debates. JMIR Public Health and Surveillance 2016;2(2):e153 View
  2. Lwin M, Lu J, Sheldenkar A, Cayabyab Y, Yee A, Smith H. Temporal and textual analysis of social media on collective discourses during the Zika virus pandemic. BMC Public Health 2020;20(1) View
  3. Kim Y, Kim J. Using photos for public health communication: A computational analysis of the Centers for Disease Control and Prevention Instagram photos and public responses. Health Informatics Journal 2020;26(3):2159 View
  4. Meleo-Erwin Z, Basch C, MacLean S, Scheibner C, Cadorett V. “To each his own”: Discussions of vaccine decision-making in top parenting blogs. Human Vaccines & Immunotherapeutics 2017;13(8):1895 View
  5. Kim J, Park J, Park E, Ji S. Analysis of issues and trends in cosmetic plastic procedures using tweets from Twitters. Public Health Affairs 2017;1(1):129 View
  6. Nguyen J, Gilbert L, Priede L, Heckman C. The Reach of the “Don’t Fry Day” Twitter Campaign: Content Analysis. JMIR Dermatology 2019;2(1):e14137 View
  7. Deiner M, Fathy C, Kim J, Niemeyer K, Ramirez D, Ackley S, Liu F, Lietman T, Porco T. Facebook and Twitter vaccine sentiment in response to measles outbreaks. Health Informatics Journal 2019;25(3):1116 View
  8. Fung I, Jackson A, Mullican L, Blankenship E, Goff M, Guinn A, Saroha N, Tse Z. Contents, Followers, and Retweets of the Centers for Disease Control and Prevention’s Office of Advanced Molecular Detection (@CDC_AMD) Twitter Profile: Cross-Sectional Study. JMIR Public Health and Surveillance 2018;4(2):e33 View
  9. Lama Y, Chen T, Dredze M, Jamison A, Quinn S, Broniatowski D. Discordance Between Human Papillomavirus Twitter Images and Disparities in Human Papillomavirus Risk and Disease in the United States: Mixed-Methods Analysis. Journal of Medical Internet Research 2018;20(9):e10244 View
  10. Vraga E, Bode L. I do not believe you: how providing a source corrects health misperceptions across social media platforms. Information, Communication & Society 2018;21(10):1337 View
  11. Neumayer C, Rossi L. Images of protest in social media: Struggle over visibility and visual narratives. New Media & Society 2018;20(11):4293 View
  12. Mitran C, Mitran M, Tampa M, Georgescu S, Popa M. Communication – a key element in vaccination strategies. Infectio.ro 2018;2(54):13 View
  13. Barros J, Duggan J, Rebholz-Schuhmann D. The Application of Internet-Based Sources for Public Health Surveillance (Infoveillance): Systematic Review. Journal of Medical Internet Research 2020;22(3):e13680 View
  14. Cacciatore M, Nowak G, Evans N. It's Complicated: The 2014–2015 U.S. Measles Outbreak and Parents’ Vaccination Beliefs, Confidence, and Intentions. Risk Analysis 2018;38(10):2178 View
  15. Bartolini I, Patella M. Real-Time Stream Processing in Social Networks with RAM3S. Future Internet 2019;11(12):249 View
  16. MacDougall D, Langley J, Li L, Ye L, MacKinnon-Cameron D, Top K, McNeil S, Halperin B, Swain A, Bettinger J, Dubé E, De Serres G, Halperin S. Knowledge, attitudes, beliefs, and behaviors of university students, faculty, and staff during a meningococcal serogroup B outbreak vaccination program. Vaccine 2017;35(18):2520 View
  17. Bode L, Vraga E. See Something, Say Something: Correction of Global Health Misinformation on Social Media. Health Communication 2018;33(9):1131 View
  18. Chen T, Dredze M. Vaccine Images on Twitter: Analysis of What Images are Shared. Journal of Medical Internet Research 2018;20(4):e130 View
  19. Marcon A, Caulfield T, Schumacher U. Commenting on chiropractic: A YouTube analysis. Cogent Medicine 2017;4(1):1277450 View
  20. Raghupathi V, Ren J, Raghupathi W. Studying Public Perception about Vaccination: A Sentiment Analysis of Tweets. International Journal of Environmental Research and Public Health 2020;17(10):3464 View
  21. Buente W, Rathnayake C, Neo R, Dalisay F, Kramer H. Tradition Gone Mobile: An Exploration of #Betelnut on Instagram. Substance Use & Misuse 2020;55(9):1483 View
  22. Wang Y, McKee M, Torbica A, Stuckler D. Systematic Literature Review on the Spread of Health-related Misinformation on Social Media. Social Science & Medicine 2019;240:112552 View
  23. Wang Y, Fikis D. Common Core State Standards on Twitter: Public Sentiment and Opinion Leaders. Educational Policy 2019;33(4):650 View
  24. Mavragani A. Infodemiology and Infoveillance: Scoping Review. Journal of Medical Internet Research 2020;22(4):e16206 View
  25. Francia M, Gallinucci E, Golfarelli M. Social BI to understand the debate on vaccines on the Web and social media: unraveling the anti-, free, and pro-vax communities in Italy. Social Network Analysis and Mining 2019;9(1) View
  26. Tangherlini T, Roychowdhury V, Glenn B, Crespi C, Bandari R, Wadia A, Falahi M, Ebrahimzadeh E, Bastani R. “Mommy Blogs” and the Vaccination Exemption Narrative: Results From A Machine-Learning Approach for Story Aggregation on Parenting Social Media Sites. JMIR Public Health and Surveillance 2016;2(2):e166 View
  27. Pang R, Wei Z, Liu W, Chen Z, Cheng X, Zhang H, Li G, Liu L. Influence of the pandemic dissemination of COVID‐19 on facial rejuvenation: A survey of Twitter. Journal of Cosmetic Dermatology 2020;19(11):2778 View
  28. Gastañaduy P, Banerjee E, DeBolt C, Bravo-Alcántara P, Samad S, Pastor D, Rota P, Patel M, Crowcroft N, Durrheim D. Public health responses during measles outbreaks in elimination settings: Strategies and challenges. Human Vaccines & Immunotherapeutics 2018;14(9):2222 View
  29. Yuan X, Schuchard R, Crooks A. Examining Emergent Communities and Social Bots Within the Polarized Online Vaccination Debate in Twitter. Social Media + Society 2019;5(3):205630511986546 View
  30. Smith C, Seitz H. Correcting Misinformation About Neuroscience via Social Media. Science Communication 2019;41(6):790 View
  31. Oh H, Lee H. When Do People Verify and Share Health Rumors on Social Media? The Effects of Message Importance, Health Anxiety, and Health Literacy. Journal of Health Communication 2019;24(11):837 View
  32. Kim I, Feng C, Wang Y, Spitzberg B, Tsou M. Exploratory Spatiotemporal Analysis in Risk Communication during the MERS Outbreak in South Korea. The Professional Geographer 2017;69(4):629 View
  33. Stefanidis A, Vraga E, Lamprianidis G, Radzikowski J, Delamater P, Jacobsen K, Pfoser D, Croitoru A, Crooks A. Zika in Twitter: Temporal Variations of Locations, Actors, and Concepts. JMIR Public Health and Surveillance 2017;3(2):e22 View
  34. Du L, Rachul C, Guo Z, Caulfield T. Gordie Howe’s “Miraculous Treatment”: Case Study of Twitter Users’ Reactions to a Sport Celebrity’s Stem Cell Treatment. JMIR Public Health and Surveillance 2016;2(1):e8 View
  35. Anguera M, Portell M, Chacón-Moscoso S, Sanduvete-Chaves S. Indirect Observation in Everyday Contexts: Concepts and Methodological Guidelines within a Mixed Methods Framework. Frontiers in Psychology 2018;9 View
  36. van Lent L, Sungur H, Kunneman F, van de Velde B, Das E. Too Far to Care? Measuring Public Attention and Fear for Ebola Using Twitter. Journal of Medical Internet Research 2017;19(6):e193 View
  37. 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
  38. Rousidis D, Koukaras P, Tjortjis C. Social media prediction: a literature review. Multimedia Tools and Applications 2020;79(9-10):6279 View
  39. Lwin M, Lu J, Sheldenkar A, Schulz P. Strategic Uses of Facebook in Zika Outbreak Communication: Implications for the Crisis and Emergency Risk Communication Model. International Journal of Environmental Research and Public Health 2018;15(9):1974 View
  40. Lazard A, Saffer A, Wilcox G, Chung A, Mackert M, Bernhardt J. E-Cigarette Social Media Messages: A Text Mining Analysis of Marketing and Consumer Conversations on Twitter. JMIR Public Health and Surveillance 2016;2(2):e171 View
  41. Porat T, Garaizar P, Ferrero M, Jones H, Ashworth M, Vadillo M. Content and source analysis of popular tweets following a recent case of diphtheria in Spain. European Journal of Public Health 2019;29(1):117 View
  42. Bridgman A, Merkley E, Zhilin O, Loewen P, Owen T, Ruths D. Infodemic Pathways: Evaluating the Role That Traditional and Social Media Play in Cross-National Information Transfer. Frontiers in Political Science 2021;3 View
  43. Du J, Luo C, Shegog R, Bian J, Cunningham R, Boom J, Poland G, Chen Y, Tao C. Use of Deep Learning to Analyze Social Media Discussions About the Human Papillomavirus Vaccine. JAMA Network Open 2020;3(11):e2022025 View
  44. Gallagher J, Lawrence H. Rhetorical Appeals and Tactics in New York Times Comments About Vaccines: Qualitative Analysis. Journal of Medical Internet Research 2020;22(12):e19504 View
  45. Karafillakis E, Martin S, Simas C, Olsson K, Takacs J, Dada S, Larson H. Methods for Social Media Monitoring Related to Vaccination: Systematic Scoping Review. JMIR Public Health and Surveillance 2021;7(2):e17149 View
  46. Yahata Y, Fielding J, Kamiya H, Takimoto N, Ishii J, Fukusumi M, Sunagawa T. Factors associated with knowledges and attitudes about measles and rubella immunization in a non-health care occupational setting in Japan. Journal of Infection and Chemotherapy 2021;27(5):684 View
  47. Prieto Santamaría L, Tuñas J, Fernández Peces-Barba D, Jaramillo A, Cotarelo M, Menasalvas E, Conejo Fernández A, Arce A, Gil de Miguel A, Rodríguez González A. Influenza and Measles-MMR: two case study of the trend and impact of vaccine-related Twitter posts in Spanish during 2015-2018. Human Vaccines & Immunotherapeutics 2022;18(1):1 View
  48. Kim Y, Song D, Lee Y. #Antivaccination on Instagram: A Computational Analysis of Hashtag Activism through Photos and Public Responses. International Journal of Environmental Research and Public Health 2020;17(20):7550 View
  49. Shakeri S. A Framework for the Interaction of Active Audiences and Influencers on Twitter: The Case of Zika Virus. Journal of Information & Knowledge Management 2020;19(04):2050032 View
  50. Thelwall M, Kousha K, Thelwall S. Covid-19 vaccine hesitancy on English-language Twitter. El profesional de la información 2021 View
  51. Suarez-Lledo V, Alvarez-Galvez J. Prevalence of Health Misinformation on Social Media: Systematic Review. Journal of Medical Internet Research 2021;23(1):e17187 View
  52. Featherstone J, Barnett G, Ruiz J, Zhuang Y, Millam B. Exploring childhood anti-vaccine and pro-vaccine communities on twitter – a perspective from influential users. Online Social Networks and Media 2020;20:100105 View
  53. Lynch M, Knezevic I, Ryan K, Cahill N. Opportunities for Qualitative Analysis of Social Media Platforms in Dietetic Research and Practice. Canadian Journal of Dietetic Practice and Research 2021;82(2):79 View
  54. Fazel S, Quinn E, Ford-Sahibzada C, Szarka S, Peters C. Sunscreen Posts on Twitter in the United States and Canada, 2019: Content Analysis. JMIR Dermatology 2021;4(2):e29723 View
  55. Alfatease A, Alqahtani A, Orayj K, Alshahrani S. The Impact of Social Media on the Acceptance of the COVID-19 Vaccine: A Cross-Sectional Study from Saudi Arabia. Patient Preference and Adherence 2021;Volume 15:2673 View
  56. Doll M, Correira J. Revisiting the 2014-15 Disneyland measles outbreak and its influence on pediatric vaccinations. Human Vaccines & Immunotherapeutics 2021;17(11):4210 View
  57. Mishra S, Verma A, Meena K, Kaushal R. Public reactions towards Covid-19 vaccination through twitter before and after second wave in India. Social Network Analysis and Mining 2022;12(1) View
  58. Thakur N, Han C. An Exploratory Study of Tweets about the SARS-CoV-2 Omicron Variant: Insights from Sentiment Analysis, Language Interpretation, Source Tracking, Type Classification, and Embedded URL Detection. COVID 2022;2(8):1026 View
  59. Liu X, Alsghaier H, Tong L, Ataullah A, McRoy S. Visualizing the Interpretation of a Criteria-Driven System That Automatically Evaluates the Quality of Health News: Exploratory Study of 2 Approaches. JMIR AI 2022;1(1):e37751 View
  60. Chen Q, Crooks A. Analyzing the vaccination debate in social media data Pre- and Post-COVID-19 pandemic. International Journal of Applied Earth Observation and Geoinformation 2022;110:102783 View
  61. Choudhury N. Ageing, health misinformation and mobile messaging apps. Catalan Journal of Communication & Cultural Studies 2021;13(2):233 View
  62. Engel-Rebitzer E, Stokes D, Meisel Z, Purtle J, Doyle R, Buttenheim A. Partisan Differences in Legislators’ Discussion of Vaccination on Twitter During the COVID-19 Era: Natural Language Processing Analysis. JMIR Infodemiology 2022;2(1):e32372 View
  63. Luo C, Chen A, Cui B, Liao W. Exploring public perceptions of the COVID-19 vaccine online from a cultural perspective: Semantic network analysis of two social media platforms in the United States and China. Telematics and Informatics 2021;65:101712 View
  64. Hu Z, Ma B, Bai R. Motivation to participate in secondary science communication. Frontiers in Psychology 2022;13 View
  65. PAKKAN Ş. İnfodemik Dünya: Sağlık Habercilerinin Pandemi Sürecinde İnfodemiye İlişkin Tespit ve Önerileri. İletişim Kuram ve Araştırma Dergisi 2021;2021(55):56 View
  66. Lynch M, Knezevic I, Mah C. Exploring food shopping behaviours through a study of Ottawa social media. Appetite 2022;168:105695 View
  67. Haggerty T, Sedney C, Cowher A, Holland D, Davisson L, Dekeseredy P. Twitter and Communicating Stigma about Medications to Treat Obesity. Health Communication 2023;38(14):3238 View
  68. Walter D, Ophir Y, Lokmanoglu A, Pruden M. Vaccine discourse in white nationalist online communication: A mixed-methods computational approach. Social Science & Medicine 2022;298:114859 View
  69. López-Rodríguez G, Castillo-Eslava F. A Comparative Study of Military Communication on Instagram: A Research Note. Armed Forces & Society 2024;50(3):810 View
  70. Khademi Habibabadi S, Delir Haghighi P, Burstein F, Buttery J. Vaccine Adverse Event Mining of Twitter Conversations: 2-Phase Classification Study. JMIR Medical Informatics 2022;10(6):e34305 View
  71. Batool S, Ahmed W, Mahmood K, Sharif A. Social network analysis of Twitter data from Pakistan during COVID-19. Information Discovery and Delivery 2022;50(4):353 View
  72. Mittal R, Mittal A, Aggarwal I. Identification of affective valence of Twitter generated sentiments during the COVID-19 outbreak. Social Network Analysis and Mining 2021;11(1) View
  73. Sano Y, Hori A, Kolahi J. 12-year observation of tweets about rubella in Japan: A retrospective infodemiology study. PLOS ONE 2023;18(5):e0285101 View
  74. Coulibaly S. Exploring health misinformation on WhatsApp within the African migrant and refugee community in Southeast Queensland (SEQ). Media International Australia 2023;189(1):8 View
  75. Singh L, Gresenz C. Social Media Data for Firearms Research: Promise and Perils. The ANNALS of the American Academy of Political and Social Science 2022;704(1):267 View
  76. Thakur N. Investigating and Analyzing Self-Reporting of Long COVID on Twitter: Findings from Sentiment Analysis. Applied System Innovation 2023;6(5):92 View
  77. Thakur N, Duggal Y, Liu Z. Analyzing Public Reactions, Perceptions, and Attitudes during the MPox Outbreak: Findings from Topic Modeling of Tweets. Computers 2023;12(10):191 View
  78. Thakur N. Sentiment Analysis and Text Analysis of the Public Discourse on Twitter about COVID-19 and MPox. Big Data and Cognitive Computing 2023;7(2):116 View
  79. Silva M, Skeva R, House T, Jay C. Tracking the structure and sentiment of vaccination discussions on Mumsnet. Social Network Analysis and Mining 2023;13(1) View
  80. Terry K, Yang F, Yao Q, Liu C. The role of social media in public health crises caused by infectious disease: a scoping review. BMJ Global Health 2023;8(12):e013515 View
  81. Huang L, Eiden A, He L, Annan A, Wang S, Wang J, Manion F, Wang X, Du J, Yao L. Natural Language Processing–Powered Real-Time Monitoring Solution for Vaccine Sentiments and Hesitancy on Social Media: System Development and Validation. JMIR Medical Informatics 2024;12:e57164 View
  82. Shapiro G, Surian D, Dunn A, Perry R, Kelaher M. Comparing human papillomavirus vaccine concerns on Twitter: a cross-sectional study of users in Australia, Canada and the UK. BMJ Open 2017;7(10):e016869 View
  83. Sasse K, Mahabir R, Gkountouna O, Crooks A, Croitoru A, Koh K. Understanding the determinants of vaccine hesitancy in the United States: A comparison of social surveys and social media. PLOS ONE 2024;19(6):e0301488 View

Books/Policy Documents

  1. Koukaras P, Rousidis D, Tjortjis C. Advanced Computational Intelligence in Healthcare-7. View
  2. Samaras L, García-Barriocanal E, Sicilia M. Innovation in Health Informatics. View
  3. Rodríguez-Medina J, Rodríguez-Triana M, Eradze M, García-Sastre S. Lifelong Technology-Enhanced Learning. View
  4. Selkälä A, Callegaro M, Couper M. Social Computing and Social Media. Design, Ethics, User Behavior, and Social Network Analysis. View
  5. Leightley D, Sharp M, Williamson V, Fear N, Gribble R. Social Media and the Armed Forces. View
  6. Rutledge P. The International Encyclopedia of Media Psychology. View
  7. Leightley D, Sharp M, Williamson V, Fear N, Gribble R. Soziale Medien und die Streitkräfte. View
  8. Walter D, Ophir Y. Vaccine Communication Online. View