Influence of online opinions and interactions on the Covid-19 vaccination in Chile
Identifikátory výsledku
Kód výsledku v IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11320%2F22%3AY7Y29US2" target="_blank" >RIV/00216208:11320/22:Y7Y29US2 - isvavai.cz</a>
Výsledek na webu
<a href="https://www.nature.com/articles/s41598-022-23738-0" target="_blank" >https://www.nature.com/articles/s41598-022-23738-0</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1038/s41598-022-23738-0" target="_blank" >10.1038/s41598-022-23738-0</a>
Alternativní jazyky
Jazyk výsledku
angličtina
Název v původním jazyce
Influence of online opinions and interactions on the Covid-19 vaccination in Chile
Popis výsledku v původním jazyce
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.
Název v anglickém jazyce
Influence of online opinions and interactions on the Covid-19 vaccination in Chile
Popis výsledku anglicky
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.
Klasifikace
Druh
J<sub>SC</sub> - Článek v periodiku v databázi SCOPUS
CEP obor
—
OECD FORD obor
10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
Návaznosti výsledku
Projekt
—
Návaznosti
—
Ostatní
Rok uplatnění
2022
Kód důvěrnosti údajů
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Údaje specifické pro druh výsledku
Název periodika
Scientific Reports
ISSN
2045-2322
e-ISSN
2045-2322
Svazek periodika
12
Číslo periodika v rámci svazku
1
Stát vydavatele periodika
GB - Spojené království Velké Británie a Severního Irska
Počet stran výsledku
13
Strana od-do
1-13
Kód UT WoS článku
—
EID výsledku v databázi Scopus
2-s2.0-85143617416