RESUMO
We analyze 6 months of Twitter conversations related to the Chilean Covid-19 vaccination process, in order to understand the online forces that argue for or against it and suggest effective digital communication strategies. Using AI, we classify accounts into four categories that emerge from the data as a result of the type of language used. This classification naturally distinguishes pro- and anti-vaccine activists from moderates that promote or inhibit vaccination in discussions, which also play a key role that should be addressed by public policies. We find that all categories display relatively constant opinions, but that the number of tweeting accounts grows in each category during controversial periods. We also find that accounts disfavoring vaccination tend to appear in the periphery of the interaction network, which is consistent with Chile's high immunization levels. However, these are more active in addressing those favoring vaccination than vice-versa, revealing a potential communication problem even in a society where the antivaccine movement has no central role. Our results highlight the importance of social network analysis to understand public discussions and suggest online interventions that can help achieve successful immunization campaigns.
