Sentiment Analysis Using Machine Learning and Deep Learning on Covid 19 Vaccine Twitter Data with Hadoop MapReduce

被引：0

作者：

Kul, Seda ^{[1
]}

Sayar, Ahmet ^{[1
]}

机构：

[1] Kocaeli Univ, Baki Komsuoglu Bulvari 515, TR-41001 Kocaeli, Turkey

来源：

6TH INTERNATIONAL CONFERENCE ON SMART CITY APPLICATIONS | 2022年 / 393卷

关键词：

Coronavirus; Twitter; Sentiment analysis; Natural language processing; Big data; Distributed systems; Hadoop; MapReduce; Machine learning; Deep learning;

D O I：

10.1007/978-3-030-94191-8_69

中图分类号：

TP39 [计算机的应用];

学科分类号：

081203 ; 0835 ;

摘要：

The Coronavirus, also known as COVID-19, initially surfaced in Wuhan, China, in December of 2019. The virus was one of the most widely discussed subjects on social media. As a result, these social media sources are exposed to and present a variety of viewpoints, beliefs, and feelings. Big data is a significant resource for computer scientists and scholars who want to understand how people feel about current events. We present a real-time implementation of a system that can identify Twitter opinions about the COVID-19 Vaccine using Hadoop in this work. All tweets are divided into three categories (Positive, Neutral, and Negative). Sentiment analysis was conducted by Logistic Regression, Random Forest, Deep Neural Network, and Convolutional Neural Network.

引用

页码：859 / 868

页数：10

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