Version 1
: Received: 14 May 2022 / Approved: 19 May 2022 / Online: 19 May 2022 (03:42:40 CEST)
How to cite:
Obu, U.; Thakur, S. COVID-19 Real Time Live Tweet Sentimental Analysis Using Deep Learning Methods, Its Effect on Phases of COVID-19 Waves. Preprints2022, 2022050248. https://doi.org/10.20944/preprints202205.0248.v1
Obu, U.; Thakur, S. COVID-19 Real Time Live Tweet Sentimental Analysis Using Deep Learning Methods, Its Effect on Phases of COVID-19 Waves. Preprints 2022, 2022050248. https://doi.org/10.20944/preprints202205.0248.v1
Obu, U.; Thakur, S. COVID-19 Real Time Live Tweet Sentimental Analysis Using Deep Learning Methods, Its Effect on Phases of COVID-19 Waves. Preprints2022, 2022050248. https://doi.org/10.20944/preprints202205.0248.v1
APA Style
Obu, U., & Thakur, S. (2022). COVID-19 Real Time Live Tweet Sentimental Analysis Using Deep Learning Methods, Its Effect on Phases of COVID-19 Waves. Preprints. https://doi.org/10.20944/preprints202205.0248.v1
Chicago/Turabian Style
Obu, U. and Shruti Thakur. 2022 "COVID-19 Real Time Live Tweet Sentimental Analysis Using Deep Learning Methods, Its Effect on Phases of COVID-19 Waves" Preprints. https://doi.org/10.20944/preprints202205.0248.v1
Abstract
The Covid-19 also known as the Coronavirus is a viral disease from the SARS-CoV-2 family of virus, as at December 2019 the first case of this virus infection was identified at Wuhan, China, this seemingly isolated case soon became a global pandemic, whose effect was felt globally which also had colossal effects on both health, economic and politics . As at the time of this research about 4.5 million people have died of the Coronavirus and over 215 million people already infected by it. This pandemic stood out not just for its scale but for how social media was a major contribution to its spread as well as to curbing it. The power of social media was used to spread misinformation as well as to spread awareness on the subject, with both having massive impact on the people. In this paper we will be running a sentimental analysis on twitter under the keyword “Covid-19 and Coronavirus”, twitter is a powerful social media tool that is known for its ability to keep trends in the form of tweets, we will be drawing correlations between the peaks of tweet with the peak of infection. We will also be analyzing to know what the impact of these tweets are having on the rate of the infection and vice versa. We will also be analyzing what people are tweeting most about, what are the talking points, comparing both real time and past tweets with real time infection and death rates using deep different learning methods to access what information can be derived from it.
Keywords
COVID-19; sentiment analysis; deep learning
Subject
Computer Science and Mathematics, Artificial Intelligence and Machine Learning
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
