Text Analysis of COVID-19 Tweets
Engineering Applications of Neural Networks, Eaaai/Eann 2022
; 1600:517-528, 2022.
Article
in English
| Web of Science | ID: covidwho-2311292
ABSTRACT
During the COVID-19 pandemic many countries were forced to implement lockdowns to prevent further spread of the SARS-CoV-2, prohibiting people from face-to-face social interactions. This unprecedented circumstance led to an increase in traffic on social media platforms, one of the most popular of which is Twitter, with a diverse spectrum of users from around the world. This quality, along with the ability to use its API for research purposes, makes it a valuable resource for data collection and analysis. In this paper we aim to present the sentiments towards the COVID-19 pandemic and vaccines as it was imprinted through the users' tweets when the events were actually still in motion. For our research, we gathered the related data from Twitter and characterized the gathered tweets in two classes, positive and negative;using the BERT model, with an accuracy of 99%. Finally, we performed various time series analyses based on people's sentiment with reference to the pandemic period of 2021, the four major vaccine's companies as well as on the vaccine's technology.
Full text:
Available
Collection:
Databases of international organizations
Database:
Web of Science
Language:
English
Journal:
Eann 2022
Year:
2022
Document Type:
Article
Similar
MEDLINE
...
LILACS
LIS