Inferring COVID-19 Vaccine Attitudes from Twitter Data : An Application to the Arabic Speaking World

Inferring COVID-19 Vaccine Attitudes from Twitter Data : An Application to the Arabic Speaking World

This study investigates whether Twitter data can be used to infer attitudes towards COVID-19 vaccination with an application to the Arabic speaking world. At first glance, anti-vaccine sentiment estimated from Twitter data is surprisingly low in co...

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Bibliographic Details
Main Author: Van Der Weide, Roy
Format: Working Paper
Language:English
English
Published: World Bank, Washington, DC 2022
Subjects:
VACCINE SENTIMENT
ARABIC TWITTER SENTIMENT DATA
ANTI-VACCINE SOCIAL MEDIA
COVID VACCINE SIDE EFFECT ATTITUDES
SOCIAL MEDIA VACCINE ENDORSEMENTS
POSITIVE VACCINE MESSAGING
COVID-19 PANDEMIC
HEALTH BEHAVIOR
PUBLIC HEALTH PROMOTION
PUBLIC HEALTH SURVEY VS TWITTER DATA
Online Access:http://documents.worldbank.org/curated/en/099545109062215988/IDU09209a2550575104cbf0b5dc0990c0568bc5a
http://hdl.handle.net/10986/37970

Internet

http://documents.worldbank.org/curated/en/099545109062215988/IDU09209a2550575104cbf0b5dc0990c0568bc5a
http://hdl.handle.net/10986/37970

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