A Hybrid Approach to Explore Public Sentiments on COVID-19
Text processing methods like lexicon-based unsupervised approaches play important roles to quantify public opinions in the textual domain. While these methods have benefit to directly generate sentiment scores from text data based on the word-intensity scores, they perform poorly with shorter unstru...
Main Author: | Bashar, M.K (Author) |
---|---|
Format: | Article |
Language: | English |
Published: |
Springer
2022
|
Subjects: | |
Online Access: | View Fulltext in Publisher |
Similar Items
-
Public Perceptions of COVID-19 Vaccines: Policy Implications from US Spatiotemporal Sentiment Analytics
by: G. G. Md. Nawaz Ali, et al.
Published: (2021-08-01) -
Exploring discussions of health and risk and public sentiment in Massachusetts during COVID-19 pandemic mandate implementation: A Twitter analysis
by: Danyellé Thorpe Huerta, et al.
Published: (2021-09-01) -
ONLINE FORECASTING OF COVID-19 CASES IN NIGERIA USING LIMITED DATA
by: Kabir Abdulmajeed, et al.
Published: (2020-06-01) -
Public Opinions about Online Learning during COVID-19: A Sentiment Analysis Approach
by: Kaushal Kumar Bhagat, et al.
Published: (2021-03-01) -
Exploring the Initial Impact of COVID-19 Sentiment on US Stock Market Using Big Data
by: Hee Soo Lee
Published: (2020-08-01)