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Network analysis, quantitative analysis, misinformation, virtual communities, social media, critical thinking
Andre, F.E., Booy, R., Bock, H.L., Clemens, J., Datta, S. K., John, T.J., Lee, B.W., Lolekha, S., Peltola, H., Ruff, T.A., Santosham, M., & Schmitt, H.J. (2008). Vaccination greatly reduces disease, disability, death and inequity worldwide. Bulletin of the World Health Organization, 86(2), 140-146. https://doi.org/10.2471/BLT.07.040089
Auger, G.A. (2013). Fostering democracy through social media: Evaluating diametrically opposed nonprofit advocacy organizations’ use of Facebook, Twitter, and YouTube. Public Relations Review, 39(4), 369-376. https://doi.org/10.1016/j.pubrev.2013.07.013
Bello-Orgaz, G., Hernandez-Castro, J., & Camacho, D. (2017). Detecting discussion communities on vaccination in twitter. Future Generation Computer Systems, 66, 125-136. https://doi.org/10.1016/j.future.2016.06.032
Bertin, P., Nera, K., & Delouvée, S. (2020). Conspiracy beliefs, rejection of vaccination, and support for hydroxychloroquine: A conceptual replication-extension in the COVID-19 pandemic context. Frontiers in psychology, 11, 1-9. https://doi.org/10.3389/fpsyg.2020.565128
Bosch, T. (2017). Twitter activism and youth in South Africa: The case of #RhodesMustFall. Information, Communication & Society, 20(2), 221-232. https://doi.org/10.1080/1369118X.2016.1162829
Botometer (Ed.) (2020). Botometer® by OSoMe. FAQ. https://bit.ly/3bGEPh8
Brand, E., & Gomez, H. (2006). Análisis de redes sociales como metodología de investigación. Elementos básicos y aplicación. Repositorio Institucional Universidad de Antioquia. https://bit.ly/3npVOdi
Broniatowski, D.A., Jamison, A.M., Qi, S., AlKulaib, L., Chen, T., Benton, A., Quinn, S.C., & Dredze, M. (2018). Weaponized health communication: Twitter bots and russian trolls amplify the vaccine debate. American Journal of Public Health, 108(10), 1378-1384. https://doi.org/10.2105/AJPH.2018.304567
Burnap, P., Gibson, R., Sloan, L., Southern, R., & Williams, M. (2016). 140 characters to victory? Using Twitter to predict the UK 2015 general election. Electoral Studies, 41, 230-233. https://doi.org/10.1016/j.electstud.2015.11.017
Callaway, E. (2020). Russia announces positive COVID-vaccine results from controversial trial. Nature. https://doi.org/10.1038/d41586-020-03209-0
Centro de Investigaciones Sociológicas (CIS) (Ed.) (2021). Barómetro de febrero 2021. https://bit.ly/37LyfFj
Colleoni, E., Rozza, A., & Arvidsson, A. (2014). Echo chamber or public sphere? Predicting political orientation and measuring political homophily in Twitter using big data. Journal of Communication, 64(2), 317-332. https://doi.org/10.1111/jcom.12084
Cuesta-Cambra, U., Martínez-Martínez, L., & Niño-González, J.I. (2019). Análisis de la información pro vacunas y anti vacunas en redes sociales e internet. Patrones visuales y emocionales. Profesional de la Información, 28(2), e280217. https://doi.org/10.3145/epi.2019.mar.17
Denia, E. (2020). The impact of science communication on Twitter: The case of Neil deGrasse Tyson. [El impacto del discurso científico en Twitter: El caso de Neil deGrasse Tyson]. Comunicar, 65, 21-30. https://doi.org/10.3916/C65-2020-02
Dixon, G., & Clarke, C. (2013). The effect of falsely balanced reporting of the autism-vaccine controversy on vaccine safety perceptions and behavioral intentions. Health Education Research, 28(2), 352-359. https://doi.org/10.1093/her/cys110
Dror, A.A., Eisenbach, N., Taiber, S., Morozov, N.G., Mizrachi, M., Zigron, A., Srouji, S., & Sela, E. (2020). Vaccine hesitancy: the next challenge in the fight against COVID-19. European Journal of Epidemiology, 35, 775-779. https://doi.org/10.1007/s10654-020-00671-y
Dubé, E., Vivion, M., & MacDonald, N.E. (2015). Vaccine hesitancy, vaccine refusal and the anti-vaccine movement: Influence, impact and implications. Expert Review of Vaccines, 14(1), 99-117. https://doi.org/10.1586/14760584.2015.964212
Fauziyyah, A. (2020). Analisis sentimen pandemi Covid19 pada streaming Twitter dengan text mining Python. Jurnal Ilmiah SINUS, 18(2), 31-42. https://doi.org/10.30646/sinus.v18i2.491
Flaherty, D.K. (2011). The vaccine-autism connection: A public health crisis caused by unethical medical practices and fraudulent science. Annals of Pharmacotherapy, 45(10), 1302-1304. https://doi.org/10.1345/aph.1Q318
François, G., Duclos, P., Margolis, H., Lavanchy, D., Siegrist, C.A., Meheus, A., Lambert, P.H., Emiroglu, N., Badur, S., & Van-Damme, P. (2005). Vaccine safety controversies and the future of vaccination programs. The Pediatric Infectious Disease Journal, 24(11), 953-961. https://doi.org/10.1097/01.inf.0000183853.16113.a6
Friedrich, M.J. (2019). WHO’s Top Health Threats for 2019. JAMA, 321(11). https://doi.org/10.1001/jama.2019.1934
Gintova, M. (2019). Understanding government social media users: An analysis of interactions on immigration, refugees and citizenship Canada Twitter and Facebook. Government Information Quarterly, 36(4), 101388. https://doi.org/10.1016/j.giq.2019.06.005
Graells-Garrido, E., Baeza-Yates, R., & Lalmas, M. (2019). How representative is an abortion debate on Twitter? In P. Boldi, B. Foucault-Welles, K, Kinder-Kurlanda, & C. Wilson (Eds.), Proceedings of the 10th ACM Conference on Web Science - WebSci ’19. (pp. 133-134). Association for Computing Machinery https://doi.org/10.1145/3292522.3326057
Hansen, D., Shneiderman, B., & Smith, M.A. (2010). Analyzing social media networks with NodeXL: Insights from a connected world. Graduate Journal of Social Science. https://doi.org/10.1016/B978-0-12-382229-1.00011-4
Himelboim, I., Xiao, X., Lee, D.K.L., Wang, M.Y., & Borah, P. (2020). A social networks approach to understanding vaccine conversations on Twitter: Network clusters, sentiment, and certainty in HPV social networks. Health Communication, 35(5), 607-615. https://doi.org/10.1080/10410236.2019.1573446
Hornsey, M.J., Harris, E.A., & Fielding, K.S. (2018). The psychological roots of anti-vaccination attitudes: A 24-nation investigation. Health Psychology, 37(4), 307-315. https://doi.org/10.1037/hea0000586
Jolley, D., & Douglas, K.M. (2014). The effects of anti-vaccine conspiracy theories on vaccination intentions. PLoS ONE, 9(2), 89177. https://doi.org/10.1371/journal.pone.0089177
Kouzy, R., Abi-Jaoude, J., Kraitem, A., El-Alam, M.B., Karam, B., Adib, E., Zarka, J., Traboulsi, C., Akl, E., & Baddour, K. (2020). Coronavirus goes viral: Quantifying the COVID-19 misinformation epidemic on Twitter. Cureus, 12(3). https://doi.org/10.7759/cureus.7255
López-Rico, C.M., González-Esteban, J.L., & Hernández-Martínez, A. (2020). Consumo de información en redes sociales durante la crisis de la COVID-19 en España. Revista de Comunicación y Salud, 10(2), 461-481. https://doi.org/10.35669/rcys.2020.10(2).461-481
Loria, S. (2020). TextBlob: Simplified text processing (0.16.0). https://bit.ly/3knzFL8
Manfredi-Sánchez, J., Amado-Suárez, A., & Waisbord, S. (2021). Presidential Twitter in the face of COVID-19: Between populism and pop politics. [Twitter presidencial ante la COVID-19: Entre el populismo y la política pop]. Comunicar, 66, 83-94. https://doi.org/10.3916/C66-2021-07
McKnight, P.E., & Najab, J. (2010). Mann?Whitney U Test. In I.B. Weiner, & W.E. Craighead (Eds.), The Corsini Encyclopedia of Psychology. John Wiley & Sons. https://doi.org/10.1002/9780470479216.corpsy0524
Meyer, S.B., Violette, R., Aggarwal, R., Simeoni, M., MacDougall, H., & Waite, N. (2019). Vaccine hesitancy and Web 2.0: Exploring how attitudes and beliefs about influenza vaccination are exchanged in online threaded user comments. Vaccine, 37(13), 1769-1774. https://doi.org/10.1016/j.vaccine.2019.02.028
Micu, A., Micu, A.E., Geru, M., & Lixandroiu, R.C. (2017). Analyzing user sentiment in social media: Implications for online marketing strategy. Psychology & Marketing, 34(12), 1094-1100. https://doi.org/10.1002/mar.21049
Milani, E., Weitkamp, E., & Webb, P. (2020). The visual vaccine debate on Twitter: A social network analysis. Media and Communication, 8(2), 364–375. https://doi.org/10.17645/mac.v8i2.2847
Oliphant, T.E. (2007). Python for scientific computing. Computing in Science & Engineering, 9(3), 10-20. https://doi.org/10.1109/MCSE.2007.58
Organización de Naciones Unidas (Ed.) (2020). Covid-19. Impact of the Pandemic on Trade and Development. https://bit.ly/2R4D0Eu
Organización Mundial de la Salud (Ed.) (2020a). Cronología de la respuesta de la OMS a la COVID-19. https://bit.ly/3qV2GA7
Organización Mundial de la Salud (Ed.) (2020b). Draft landscape and tracker of COVID-19 candidate vaccines. https://bit.ly/3snMdF6
Ostertagova, E., Ostertag, O., & Kovác, J. (2014). Methodology and application of the Kruskal-Wallis test. Applied Mechanics and Materials, 611, 115-120. https://doi.org/10.4028/www.scientific.net/AMM.611.115
Poland, G.A., & Spier, R. (2010). Fear, misinformation, and innumerates: How the Wakefield paper, the press, and advocacy groups damaged the public health. Vaccine, 28(12), 2361-2362. https://doi.org/10.1016/j.vaccine.2010.02.052
Puente, S.N., Maceiras, S.D., & Romero, D.F. (2021). Twitter activism and ethical witnessing: Possibilities and challenges of feminist politics against gender-based violence. Social Science Computer Review, 39(2), 295-311. https://doi.org/10.1177/0894439319864898
Puri, N., Coomes, E.A., Haghbayan, H., & Gunaratne, K. (2020). Social media and vaccine hesitancy: New updates for the era of COVID-19 and globalized infectious diseases. Human Vaccines and Immunotherapeutics, 16(11), 1-8. https://doi.org/10.1080/21645515.2020.1780846
Schmidt, A.L., Zollo, F., Scala, A., Betsch, C., & Quattrociocchi, W. (2018). Polarization of the vaccination debate on Facebook. Vaccine, 36(25), 3606-3612. https://doi.org/10.1016/j.vaccine.2018.05.040
Serrano-Contreras, I.J., García-Marín, J., & Luengo, O.G. (2020). Measuring online political dialogue: Does polarization trigger more deliberation? Media and Communication, 8(4), 63-72. https://doi.org/10.17645/mac.v8i4.3149
Spier, R.E. (2001). Perception of risk of vaccine adverse events: A historical perspective. Vaccine, 20(1), 78-84. https://doi.org/10.1016/S0264-410X(01)00306-1
Subrahmanian, V., Azaria, A., Durst, S., Kagan, V., Galstyan, A., Lerman, K., Zhu, L., Ferrara, E., Flammini, A., & Menczer, F. (2016). The DARPA Twitter bot challenge. Computer, 49(6), 38-46. https://doi.org/10.1109/MC.2016.183
Sued-Palmeiro, G.E., & Cebral-Loureda, M. (2020). Voces autorizadas en Twitter durante la pandemia de COVID-19: Actores, léxico y sentimientos como marco interpretativo para usuarios ordinarios. Revista de Comunicación y Salud, 10(2), 549-568. https://doi.org/10.35669/rcys.2020.10(2).549-568
The American Journal of Managed Care (AJMC) (Ed.) (2020). A Timeline of COVID-19 Developments in 2020. https://bit.ly/3xZI7qk
Tomeny, T.S., Vargo, C.J., & El-Toukhy, S. (2017). Geographic and demographic correlates of autism-related anti-vaccine beliefs on Twitter, 2009-15. Social Science and Medicine, 191, 168-175. https://doi.org/10.1016/j.socscimed.2017.08.041
Tornos-Inza, E. (2020). Tasa de interacción (engagement) en Twitter. Related: Marketing. https://bit.ly/3aSs9Vj
Twitter (Ed.) (2021). Acerca de las cuentas verificadas de Twitter. https://bit.ly/3dGRmUF
Vu, H.T., Do, H.V., Seo, H., & Liu, Y. (2020). Who leads the conversation on climate change? A study of a global network of NGOS on Twitter. Environmental Communication, 14(4), 450-464. https://doi.org/10.1080/17524032.2019.1687099
World Economic Forum (Ed.) (2021). More people now plan to get a COVID-19 vaccine than in December. https://bit.ly/3r6cQ1f
Xiong, Y., Cho, M., & Boatwright, B. (2019). Hashtag activism and message frames among social movement organizations: Semantic network analysis and thematic analysis of Twitter during the #MeToo movement. Public Relations Review, 45(1), 10-23. https://doi.org/10.1016/j.pubrev.2018.10.014
Yang, S., Quan-Haase, A., & Rannenberg, K. (2017). The changing public sphere on Twitter: Network structure, elites and topics of the #righttobeforgotten. New Media & Society, 19(12), 1983-2002. https://doi.org/10.1177/1461444816651409
Yelin, D., Wirtheim, E., Vetter, P., Kalil, A.C., Bruchfeld, J., Runold, M., Guaraldi, G., Mussini, C., Gudiol, C., Pujol, M., Bandera, A., Scudeller, L., Paul, M., Kaiser, L., & Leibovici, L. (2020). Long-term consequences of COVID-19: Research needs. The Lancet Infectious Diseases, 20(10), 1115-1117. https://doi.org/10.1016/S1473-3099(20)30701-5
YouGov (Ed.). (2021). COVID-19 Public Monitor. COVID-19 Public Monitor. https://yougov.co.uk/COVID-19
Zimmer, C., Corum, J., & Wee, S.L. (2021, January 11). Coronavirus vaccine tracker. The New York Times. https://nyti.ms/2NCtMxI