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Citing this Article

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Published on 04.01.16 in Vol 2, No 1 (2016): Jan-Jun

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

Works citing "The Measles Vaccination Narrative in Twitter: A Quantitative Analysis"

According to Crossref, the following articles are citing this article (DOI 10.2196/publichealth.5059):

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

  1. Barros JM, 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
    CrossRef
  2. Lwin MO, Lu J, Sheldenkar A, Cayabyab YM, Yee AZH, Smith HE. Temporal and textual analysis of social media on collective discourses during the Zika virus pandemic. BMC Public Health 2020;20(1)
    CrossRef
  3. Kim Y, Kim JH. 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;:146045821989667
    CrossRef
  4. Mavragani A. Infodemiology and Infoveillance: Scoping Review. Journal of Medical Internet Research 2020;22(4):e16206
    CrossRef
  5. Buente W, Rathnayake C, Neo R, Dalisay F, Kramer HK. Tradition Gone Mobile: An Exploration of #Betelnut on Instagram. Substance Use & Misuse 2020;55(9):1483
    CrossRef
  6. 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
    CrossRef
  7. Rousidis D, Koukaras P, Tjortjis C. Social media prediction: a literature review. Multimedia Tools and Applications 2020;79(9-10):6279
    CrossRef
  8. 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)
    CrossRef
  9. Wang Y, Fikis DJ. Common Core State Standards on Twitter: Public Sentiment and Opinion Leaders. Educational Policy 2019;33(4):650
    CrossRef
  10. 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
    CrossRef
  11. 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
    CrossRef
  12. Bartolini I, Patella M. Real-Time Stream Processing in Social Networks with RAM3S. Future Internet 2019;11(12):249
    CrossRef
  13. Porat T, Garaizar P, Ferrero M, Jones H, Ashworth M, Vadillo MA. Content and source analysis of popular tweets following a recent case of diphtheria in Spain. European Journal of Public Health 2019;29(1):117
    CrossRef
  14. Oh HJ, 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
    CrossRef
  15. 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
    CrossRef
  16. Deiner MS, Fathy C, Kim J, Niemeyer K, Ramirez D, Ackley SF, Liu F, Lietman TM, Porco TC. Facebook and Twitter vaccine sentiment in response to measles outbreaks. Health Informatics Journal 2019;25(3):1116
    CrossRef
  17. Yuan X, Schuchard RJ, Crooks AT. Examining Emergent Communities and Social Bots Within the Polarized Online Vaccination Debate in Twitter. Social Media + Society 2019;5(3):205630511986546
    CrossRef
  18. Smith CN, Seitz HH. Correcting Misinformation About Neuroscience via Social Media. Science Communication 2019;41(6):790
    CrossRef
  19. Anguera MT, 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
    CrossRef
  20. 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
    CrossRef
  21. Gastañaduy PA, Banerjee E, DeBolt C, Bravo-Alcántara P, Samad SA, Pastor D, Rota PA, Patel M, Crowcroft NS, Durrheim DN. Public health responses during measles outbreaks in elimination settings: Strategies and challenges. Human Vaccines & Immunotherapeutics 2018;14(9):2222
    CrossRef
  22. Chen T, Dredze M. Vaccine Images on Twitter: Analysis of What Images are Shared. Journal of Medical Internet Research 2018;20(4):e130
    CrossRef
  23. Lama Y, Chen T, Dredze M, Jamison A, Quinn SC, Broniatowski DA. 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
    CrossRef
  24. Bode L, Vraga EK. See Something, Say Something: Correction of Global Health Misinformation on Social Media. Health Communication 2018;33(9):1131
    CrossRef
  25. Cacciatore MA, Nowak GJ, Evans NJ. It's Complicated: The 2014-2015 U.S. Measles Outbreak and Parents’ Vaccination Beliefs, Confidence, and Intentions. Risk Analysis 2018;38(10):2178
    CrossRef
  26. Fung IC, Jackson AM, Mullican LA, Blankenship EB, Goff ME, Guinn AJ, Saroha N, Tse ZTH. 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
    CrossRef
  27. Mitran CI, Mitran MI, Tampa M, Georgescu SR, Popa MI. Communication – a key element in vaccination strategies. Infectio.ro 2018;2(54):13
    CrossRef
  28. Neumayer C, Rossi L. Images of protest in social media: Struggle over visibility and visual narratives. New Media & Society 2018;20(11):4293
    CrossRef
  29. Vraga EK, 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
    CrossRef
  30. 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
    CrossRef
  31. van Lent LG, Sungur H, Kunneman FA, 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
    CrossRef
  32. Marcon AR, Caulfield T, Schumacher U. Commenting on chiropractic: A YouTube analysis. Cogent Medicine 2017;4(1)
    CrossRef
  33. Stefanidis A, Vraga E, Lamprianidis G, Radzikowski J, Delamater PL, Jacobsen KH, 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
    CrossRef
  34. Kim I, Feng C, Wang Y, Spitzberg BH, Tsou M. Exploratory Spatiotemporal Analysis in Risk Communication during the MERS Outbreak in South Korea. The Professional Geographer 2017;69(4):629
    CrossRef
  35. Kim JY, Park J, Park E, Ji SM. Analysis of issues and trends in cosmetic plastic procedures using tweets from Twitters. Public Health Affairs 2017;1(1):129
    CrossRef
  36. Meleo-Erwin Z, Basch C, MacLean SA, Scheibner C, Cadorett V. “To each his own”: Discussions of vaccine decision-making in top parenting blogs. Human Vaccines & Immunotherapeutics 2017;13(8):1895
    CrossRef
  37. 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
    CrossRef
  38. Lazard AJ, Saffer AJ, Wilcox GB, Chung AD, Mackert MS, Bernhardt JM. 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
    CrossRef
  39. Tangherlini TR, Roychowdhury V, Glenn B, Crespi CM, 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
    CrossRef
  40. Marcon AR, 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
    CrossRef

According to Crossref, the following books are citing this article (DOI 10.2196/publichealth.5059)

:
  1. Samaras L, García-Barriocanal E, Sicilia M. Innovation in Health Informatics. 2020. :39
    CrossRef
  2. Koukaras P, Rousidis D, Tjortjis C. Advanced Computational Intelligence in Healthcare-7. 2020. Chapter 8:121
    CrossRef
  3. Rodríguez-Medina J, Rodríguez-Triana MJ, Eradze M, García-Sastre S. Lifelong Technology-Enhanced Learning. 2018. Chapter 58:617
    CrossRef