Twitter Sentiment Analysis of Covid Vaccines

Wenbo Zhu, Tiechuan Hu
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引用次数: 1

Abstract

In this paper, we look at a database of tweets sorted by various keywords that could indicate the users’ sentiment towards covid vaccines. With social media becoming such a prevalent source of opinion, sorting and ranking tweets that hold important information such as opinions on covid vaccines is of utmost importance. Two different ranking scales were used, and ranking a tweet in this way could represent the difference between an opinion being lost and an opinion being featured on the site, which affects the decisions and behavior of people, and why researchers were interested in it. Using natural language processing techniques, our aim is to determine and categorize opinions about covid vaccines with the highest accuracy possible.
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Covid疫苗的推特情绪分析
在本文中,我们研究了一个按各种关键词排序的推文数据库,这些关键词可以表明用户对covid疫苗的看法。在社交媒体成为舆论的主要来源的情况下,对包含新冠病毒疫苗等重要信息的推文进行分类和排名是非常重要的。使用了两种不同的排名量表,以这种方式对tweet进行排名可以代表一个观点被丢失和一个观点在网站上被突出的差异,这影响了人们的决策和行为,以及为什么研究人员对它感兴趣。使用自然语言处理技术,我们的目标是以尽可能高的准确性确定和分类有关covid疫苗的意见。
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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