ArticleScientific reports2022
Influence of online opinions and interactions on the Covid-19 vaccination in Chile.
Article in Scientific reports, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
3 citing papers in PubMed, 8 citations in OpenAlex.
- Routine immunization in older adults beyond COVID-19: a qualitative analysis of experiences, perceived barriers and facilitators, and recommendations for improvement.BMC geriatrics · 2026Article
- COVID-19 vaccine information disorder in Chile: a quantitative analysis of fact-checked articles.Frontiers in public health · 2025Article
- Modelling and predicting online vaccination views using bow-tie decomposition.Royal Society open science · 2024Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
8 authors at 2 institutions in 1 country.
Funding
Abstract
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.
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What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.