检疫问题:对COVID-19推文的情绪分析

2020 11th IEEE Annual Information Technology, Electronics and Mobile Communication Conference (IEMCON) Pub Date : 2020-11-04 DOI:10.1109/IEMCON51383.2020.9284875

Jason Nguyen, Ritu Chaturvedi

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引用次数: 3

摘要

随着新冠肺炎疫情的到来，人们纷纷涌向社交媒体，表达对这些不寻常情况的看法。本文旨在揭示微博平台Twitter上公众对新型冠状病毒大流行的情绪。这是通过一个拟议的算法来完成的，该算法建立在现有的基于方面的情感分析方法之上，并选择Naïve-Bayes路由来对已经被原子化成n-gram的现有tweet进行分类。这项研究得出的结论是，随着我们的隔离居民在网络平台上发表他们的争议性观点，对2020年7月新冠肺炎疫情的总体情绪是悲观和沮丧的结合。

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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Quarantine Quibbles: A Sentiment Analysis of COVID-19 Tweets

With the advent of the COVID-19 pandemic, people have flocked to social media in order to stage their thoughts surrounding these unusual circumstances. This paper aims to uncover public sentiment regarding the novel coronavirus pandemic on the microblogging platform Twitter. This is done through a proposed algorithm that builds off of existing aspect-based sentiment analysis approaches and opts for a Naïve-Bayes route to classify existing Tweets that have been atomized into n-grams. This research concludes that overall sentiment regarding the COVID-19 outbreak over July 2020 is a combination of pessimism and dejection as our quarantine denizens take to their online platforms in airing their polemic opinions.

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2020 11th IEEE Annual Information Technology, Electronics and Mobile Communication Conference (IEMCON)

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