Tweet Classification and Sentiment Analysis of Covid 19 Epidemic by Applying Hybrid Based Techniques

Mauparna Nandan, Soma Mitra, Sharmistha Dey
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引用次数: 1

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.
基于混合技术的新冠肺炎疫情推文分类与情感分析
2019冠状病毒病(COVID-19)大流行在全球范围内蔓延,使人们的正常生活中断了近两年,夺去了全球数百万人的生命。从中国武汉开始,跨越200多个国家,对卫生保健系统构成了巨大挑战。另一方面,社交媒体以前所未有的速度发展,如Twitter、Facebook、WhatsApp和Instagram等。本文的本质是根据Twitter数据提取和阐明全球人民对冠状病毒大流行的看法或情绪。该分析以词典分析和机器学习算法为基础,旨在表达对目前全球流行的冠状病毒疫情的情绪分析的最新进展,以及人们对疾病、症状、影响的认识,以及需要采取的预防措施。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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