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

共 50 条

[31] COVID-19 Data Analysis and Appropriate Vaccine Prediction using Machine Learning
Ullah, Md. Oli
Nobel, S. M. Nuruzzaman
2022 IEEE 13TH ANNUAL UBIQUITOUS COMPUTING, ELECTRONICS & MOBILE COMMUNICATION CONFERENCE (UEMCON), 2022, : 496 - 504
[32] Sentiment identification on Twitter using machine learning
Morales-Castro, Wendy
Careta, Eduardo Perez
Rayas, Angelica Hernandez
Mukhopadhyay, Tirtha Prasad
Crespo, J. Armando Perez
Cabrera, Rafael Guzman
2022 EURO-ASIA CONFERENCE ON FRONTIERS OF COMPUTER SCIENCE AND INFORMATION TECHNOLOGY, FCSIT, 2022, : 28 - 31
[33] Sentiment Analysis of Twitter Data Using Machine Learning Techniques and Scikit-learn
Elbagir, Shihab
Yang, Jing
2018 INTERNATIONAL CONFERENCE ON ALGORITHMS, COMPUTING AND ARTIFICIAL INTELLIGENCE (ACAI 2018), 2018,
[34] Sentiment Analysis on Twitter Data of World Cup Soccer Tournament Using Machine Learning
Patel, Ravikumar
Passi, Kalpdrum
IOT, 2020, 1 (02):
[35] COVID-19 Vaccine Sensing: Sentiment Analysis from Twitter Data
Xu, Han
Liu, Ruixin
Luo, Ziling
Xu, Minghua
Wang, Bang
2021 IEEE INTERNATIONAL CONFERENCE ON SYSTEMS, MAN, AND CYBERNETICS (SMC), 2021, : 3200 - 3205
[36] Performing Sentiment Analysis on Twitter Data Using Deep Learning Models: A Comparative Study
Varshney, Ashwani
Kapoor, Yatin
Thukral, Anjali
Sharma, Richa
Bedi, Punam
ADVANCES IN DATA AND INFORMATION SCIENCES, 2022, 318 : 371 - 381
[37] Covid-19 analysis by using machine and deep learning
Yadav D.
Maheshwari H.
Chandra U.
Sharma A.
Studies in Big Data, 2020, 80 : 31 - 63
[38] Twitter People's Opinions Analysis During Covid-19 Quarantine Using Machine Learning and Deep Learning Models
Alotaibi, Wafa
Alomary, Faye
Mokni, Raouia
INTELLIGENT SYSTEMS DESIGN AND APPLICATIONS, ISDA 2021, 2022, 418 : 1013 - 1024
[39] ASAVACT: Arabic sentiment analysis for vaccine-related COVID-19 tweets using deep learning
Alhumoud, Sarah
Al Wazrah, Asma
Alhussain, Laila
Alrushud, Lama
Aldosari, Atheer
Altammami, Reema Nasser
Almukirsh, Njood
Alharbi, Hind
Alshahrani, Wejdan
PEERJ COMPUTER SCIENCE, 2023, 9 : 1 - 18
[40] Using a Machine Learning Approach to Monitor COVID-19 Vaccine Adverse Events (VAE) from Twitter Data
Lian, Andrew T.
Du, Jingcheng
Tang, Lu
VACCINES, 2022, 10 (01)

← 1 2 3 4 5 →