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...

Descripció completa

Dades bibliogràfiques
Autor principal: Arañez, Glyza Marie (Autor)
Altres autors: Buenaventura, Errol (author .), Robles, Ron Martin (author .), Gomez, Clinton B. (adviser .)
Format: Thesis
Idioma:English
Matèries:
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.