Detecting vaccination information void signals a retrospective study in the Filipino Twitter space: development of social media listening system for detecting information void signals on COVID -19 vaccination

Detecting vaccination information void signals a retrospective study in the Filipino Twitter space:

Online social media platforms facilitate the spread of mis- and disinformation about COVID-19 vaccination owing partially to undetected information void signals. To detect these signals, an approach adapted from Purnat et al. (2021) involving the extraction of mass tweet quantities and natural langu...

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Detalhes bibliográficos
Autor principal: Arañez, Glyza Marie (Autor)
Outros Autores: Buenaventura, Errol (author .), Robles, Ron Martin (author .), Gomez, Clinton B. (adviser .)
Formato: Tese
Idioma:English
Assuntos:
COVID-19 (Disease) > Vaccination > Philippines.
Social media > Philippines.
Twitter > Philippines.
Public health > Philippines > Data processing.
Vaccination > Public opinion > Philippines.
Health communication > Philippines.
Information behavior > Philippines.
Web scrapping.
Natural language processing.
Topic modeling.
Information void.
Infodemic.