Mapping the anti-vaccination movement on Facebook

References

• Betsch, C., Bohm, R., & Chapman, G. B. (2015). Using behavioral insights to increase vaccination policy effectiveness. Policy Insights from the Behavioral and Brain Sciences, 2(1), 61–73.
   Google Scholar
• Betsch, C., Brewer, N. T., Brocard, P., Davies, P., Gaissmaier, W., & Haase, N. (2012). Opportunities and challenges of Web 2.0 for vaccination decisions. Vaccine, 30(25), 3727–3733.
   PubMed Web of Science ®Google Scholar
• Blei, D. M., Ng, A. Y., & Jordan, M. I. (2003). Latent dirichlet allocation. Journal of Machine Learning Research, 3(2003), 993–1022.
   Google Scholar
• Butler, R., & MacDonald, N. E. (2015). Diagnosing the determinants of vaccine hesitancy in specific subgroups: The guide to tailoring immunization programmes (TIP). Vaccine, 33(34), 4176–4179.
   PubMed Web of Science ®Google Scholar
• Camerini, L., Diviani, N., & Tardini, S. (2010). Health virtual communities: Is the self lost in the net? Social Semiotics, 20(1), 87–102.
   Google Scholar
• Cangelosi, R., & Goriely, A. (2007). Component retention in principal component analysis with application to cDNA microarray data. Biology Direct, 2(1), 2–12.
   PubMedGoogle Scholar
• Csardi, G., & Nepusz, T. (2006). The igraph software package for complex network research. InterJournal, Complex Systems, 1695. http://interjournal.org/manuscript_abstract.php?361100992
   Google Scholar
• Davies, P., Chapman, S., & Leask, J. (2002). Antivaccination activists on the world wide web. Archives of Disease in Childhood, 87(1), 22–25.
   PubMed Web of Science ®Google Scholar
• Davies, P., Chapman, S., & Leask, J. (2002). Anti-vaccination activists on the world wide web. Archives of Disease in Childhood, 87(1), 22–25.
   PubMed Web of Science ®Google Scholar
• Denzin, N. (1970). The research act in sociology. Chicago: Aldine.
   Google Scholar
• Diresta, R. and Lotan, G. (2015). Anti-vaxxers are using twitter to manipulate a vaccine bill. Retrieved from https://cran.rproject.org/web/packages/SocialMediaLab/SocialMediaLab.pdf
   Google Scholar
• Durbach, N. (2005). Bodily matters: The anti-vaccination movement in England, 1853-1907. Durham: Duke University Press.
   Google Scholar
• Graham, T. & Ackland, R. (2016). SocialMediaLab: Tools for collecting social media data and generating networks for analysis. CRAN (The Comprehensive R Archive Network). Retrieved from https://cran.rproject.org/web/packages/SocialMediaLab/SocialMediaLab.pdf
   Google Scholar
• Grant, L., Hausman, B. L., Cashion, M., Lucchesi, N., Patel, K., & Roberts, J. (2015). Vaccination persuasion online: A qualitative study of two provaccine and two vaccine-skeptical websites. Journal of Medical Internet Research, 17(5), e133.
   PubMed Web of Science ®Google Scholar
• Gray, N. J., Klein, J. D., Noyce, P. R., Sesselberg, T. S., & Cantrill, J. A. (2005). Health information-seeking behaviour inadolescence: the place of the internet. Social Science & Medicine, 60(7), 1467–1478.
   PubMed Web of Science ®Google Scholar
• Kata, A. (2010). A postmodern Pandora’s Box: Anti-vaccination misinformation on the internet. Vaccine, 28(7), 1709–1716.
   PubMed Web of Science ®Google Scholar
• Kata, A. (2012). Anti-vaccine activists, Web 2.0, and the postmodern paradigm: An overview of tactics and tropes used online by the anti-vaccination movement. Vaccine, 30(25), 3778–3789.
   PubMed Web of Science ®Google Scholar
• Klapdor, M., & Grove, A. (2015). Budget review 2015–2016 index: No Jab No Pay and other immunisation measures. Parliament of Australia. Retrieved from http://www.aph.gov.au/about_parliament/parliamentary_departments/parliamentary_library/pubs/rp/budgetreview201516/vaccination
   Google Scholar
• Kolaczyk, E. D., & Csárdi, G. (2014). Statistical analysis of network data with R. New York: Springer.
   Google Scholar
• Medved, C. E. (2016). Stay-at-home fathering as a feminist opportunity: Perpetuating, resisting, and transforming gender relations of caring and earning. Journal of Family Communication, 16(1), 16–31.
   Web of Science ®Google Scholar
• Mullen, L. 2016. Gender: Predict gender from names using historical data [R package version 0.5.2]. Retrieved from https://github.com/ropensci/gender
   Google Scholar
• Nikolenko, S. I., Koltcov, S., & Koltsova, O. (2015). Topic modelling for qualitative studies. Journal of Information Science. Advance online publication. http://jis.sagepub.com/content/early/2015/12/05/0165551515617393.full
   Web of Science ®Google Scholar
• Oh, H. J., Lauckner, C., Boehmer, J., Fewins-Bliss, R., & Li, K. (2013). Facebooking for health: An examination into the solicitation and effects of health-related social support on social networking sites. Computers in Human Behavior, 29(5), 2072–2080.
   Web of Science ®Google Scholar
• Oliver, J. E., & Wood, T. J. (2014). Conspiracy theories and the paranoid style(s) of mass opinion. American Journal of Political Science, 58(4), 952–966.
   Web of Science ®Google Scholar
• Percheski, C., & Hargittai, E. (2011). Health information-seeking in the digital age. Journal of American College Health: J of ACH, 59(5), 379–386.
   PubMed Web of Science ®Google Scholar
• Ponweiser, M. (2012). Latent dirichlet allocation in R (Diploma thesis). Institute for Statistics and Mathematics, WU (Wirtschaftsuniversität Wien), Austria. Retrieved from http://epub.wu.ac.at/3558/1/main.pdf
   Google Scholar
• Shirky, C. (2008). Here comes everybody: The power of organizing without organizations. New York: Penguin Press.
   Google Scholar
• Smith, G. J. D., & O’Malley, P. (2016). Driving politics: Data-driven governance and resistance. The British Journal of Criminology, 56(1), 1–24.
   Google Scholar
• Smith, N., Wickes, R., & Underwood, M. (2015). Managing a marginalised identity in pro-anorexia and fat acceptance cybercommunities. Journal of Sociology, 51(4), 950–967.
   Web of Science ®Google Scholar
• Teh, Y. W., Jordan, M. I., Beal, M. J., & Blei, D. M. (2006). Hierarchical dirichlet processes. Journal of the American Statistical Association, 101(476), 1566–1581.
   Web of Science ®Google Scholar
• Vaterlaus, J. M., Patten, E. V., Roche, C., & Young, J. A. (2015). Gettinghealthy: The perceived influence of socialmedia on young adult health behaviors. Computers in Human Behavior, 45, 151–157. doi: 10.1016/j.chb.2014.12.013
   Web of Science ®Google Scholar
• Watts, D. J., & Strogatz, S. H. (1998). Collective dynamics of ‘small-world’ networks. Nature, 393(6684), 440–442.
   PubMed Web of Science ®Google Scholar