在印度使用深度学习和机器学习方法对COVID-19疫苗进行意见挖掘

Balaji T.K., Annushree Bablani, Sreeja Sr
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引用次数: 0

摘要

新冠肺炎疫情发生以来,考虑到国民的意见,被认为是政府应对新冠疫情的最关键挑战,比如实施全国封锁、建立隔离程序、提供医疗服务等。此外,政府还根据民意做出了许多关键决策,以应对新冠病毒。意见挖掘或情感分析作为一种使用机器学习技术挖掘人们对几个问题的看法的方法而出现。本文在机器学习方法的支持下,通过推特提取印度民众对疫苗的看法。2021年5月4日至5月11日以及2021年8月13日至8月21日,使用最先进的机器学习和深度学习方法分析了40多万条与疫苗相关的推文。与收集到的twitter数据集上的其他模型相比,BERT和RoBERTa模型产生了有希望的结果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Opinion mining on COVID-19 vaccines in India using deep and machine learning approaches
Since the COVID-19 outbreak, considering the people’s opinion has been perceived as the most crucial challenge for the government to combat the pandemic, such as implementing a national lockdown, instituting a quarantine procedure, providing health services, and more. Furthermore, the government made many critical decisions based on public opinion to combat coronavirus. Opinion mining or sentiment analysis has arisen as a method for mining people’s views on several issues using machine learning techniques. With the support of machine learning methods, this paper extracted the Indian people’s opinions on vaccines through Twitter tweets. More than four lakh vaccine-related tweets from May 04 to May 11, 2021, and from Aug 13 to Aug 21, 2021, were analyzed using state-of-the-art machine learning and deep learning approaches. The BERT and RoBERTa models produced promising results compared to other models on the collected twitter dataset.
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