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.
Artigo
em Inglês
| 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
Texto completo:
Disponível
Coleções:
Bases de dados de organismos internacionais
Base de dados:
Scopus
Idioma:
Inglês
Revista:
3rd IEEE Conference on VLSI Device, Circuit and System, VLSI DCS 2022
Ano de publicação:
2022
Tipo de documento:
Artigo
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