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Fig. 1 | BMC Public Health

Fig. 1

From: Using text mining and sentiment analysis to analyse YouTube Italian videos concerning vaccination

Fig. 1

Co-occurrence Network (CON) based on Betweenness centrality index for Italian Youtube videos concerning vaccines in 2017 (from May to October). Nodes corresponding text in english is: “zaia” = Zaia (italian politician), “veneto” = Veneto (italian region), “vaccino = vaccine, “vaccinazione, vaccinale” = vaccinations, “treviso” = Treviso (Italian city), “tg” = newscast, “testimonianza” = evidence, “scuola” = school, “scelta” = choice, “sanità” = “risposta” = answer, “ricorso” = contestation, “proposta” = motion, “politico” = politician, “pesaro” = Pesaro (italian city where took place no-vax parade), “obbligo, obbligatorio” = compulsory, “morte” = death, “morire” = die, “morbillo” = measles, “miedico” = Miedico, “manifestazione” = manifestation, “libertà” = freedom, “iscrizione” = enrolment, “intervento” = intervention, “incontro” = meeting, “genitori” = parents, “figlio” = son, “domande” = questions, “diritto” = right, “danno” = damage, “d’anna” = D’anna (senator against vaccines), “cura” = care, “contro “= against, “confronto” = confrontation, “conferenza” = conference, “codacons” = Codacons (italian non-profit association for the protection of consumers and the environment), “certificato” = certified, “cautela” = prudence, “burioni” = Burioni (Italian medical doctor pro-vax), “bimbi” = kids, “bassano” = Bassano (italian city), “asilo” = kindergarten

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