基于推特的新冠肺炎对全球教育影响的情绪分析

Swetha Sree Cheeti, Yanyan Li, A. Hadaegh
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引用次数: 13

摘要

由于新冠肺炎在全球范围内的广泛传播,教育系统受到了严重影响。在本文中,我们对推特平台上与教育相关的推文进行了彻底的情绪分析,并得出了随着疫情在几个月内的发展,推文对人们情绪的影响的结论。通过推特,已经收集了超过9万条与世界各地教育系统变化有关的推文。使用自然语言工具包(NLTK)功能和朴素贝叶斯分类器对收集的数据集进行了情感分析。根据这项分析的结果,我们推断出新冠肺炎对教育的影响,以及人们的情绪如何因教育系统的变化而改变。因此,我们希望在这样一个前所未有的时代,在努力应对疫情的同时,更好地了解人们对教育的看法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Twitter based Sentiment Analysis of Impact of Covid-19 on Education Globaly
Education system has been gravely affected due to widespread of Covid-19 across the globe. In this paper we present a thorough sentiment analysis of tweets related to education available on twitter platform and deduce conclusions about its impact on people’s emotions as the pandemic advanced over the months. Through twitter over ninety thousand tweets have been gathered related to the circumstances involving the change in education system over the world. Using Natural language tool kit (NLTK) functionalities and Naive Bayes Classifier a sentiment analysis has been performed on the gathered dataset. Based on the results of this analysis we infer to exhibit the impact of covid-19 on education and how people’s sentiment altered due to the changes with regard to the education system. Thus, we would like to present a better understanding of people’s sentiment on education while trying to cope with the pandemic in such unprecedented times.
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