Tweet Classification and Sentiment Analysis of Covid 19 Epidemic by Applying Hybrid Based Techniques
3rd IEEE Conference on VLSI Device, Circuit and System, VLSI DCS 2022
; : 254-260, 2022.
Article
in English
| Scopus | ID: covidwho-1985510
ABSTRACT
World wide spread of COVID-19 pandemic, is throttling the normal life nearly for two years and claiming millions of life all over the globe. Starting from Wuhan of China it crosses more than 200 countries, thereby imposing a overwhelming challenge to health care system. On the other hand, there has been unprecedented advancement of the social media, namely, Twitter, Facebook, WhatsApp and Instagram etc. in an exponential manner. The essence of this paper is to extract and elucidate the opinion or sentiments of the people all around the globe regarding Coronavirus pandemic based on Twitter data. The analysis are based on both lexicon-based approach followed by machine learning algorithms and aims to express the state-of-the-art of the sentiment analysis on the current Coronavirus epidemic prevailing in the entire world and the awareness of the people regarding the disease, its symptoms and impact followed by the preventive measures that need to be undertaken. © 2022 IEEE.
COVID-19; machine learning; natural language processing (NLP); sentiment analysis; twitter; Learning algorithms; Social networking (online); Classification analysis; Coronaviruses; Healthcare systems; Language processing; Machine-learning; Natural language processing; Natural languages; Wide spreads
Full text:
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Collection:
Databases of international organizations
Database:
Scopus
Language:
English
Journal:
3rd IEEE Conference on VLSI Device, Circuit and System, VLSI DCS 2022
Year:
2022
Document Type:
Article
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