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Sentiment analysis on Covid-19 vaccine / Nur Qamarina Hamsa

The Covid-19 virus has spread to all countries over the world. In order to handle and survived through this pandemic, a vaccine for Covid-19 was developed to give body a better immune system. However, many people has different point of view towards vaccine. People tend to share their opinions on soc...

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Main Author: Hamsa, Nur Qamarina
Format: Thesis
Language:English
Published: 2021
Subjects:
Analysis
Online Access:https://ir.uitm.edu.my/id/eprint/59180/1/59180.pdf
https://ir.uitm.edu.my/id/eprint/59180/
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spelling my.uitm.ir.591802022-09-12T07:17:56Z https://ir.uitm.edu.my/id/eprint/59180/ Sentiment analysis on Covid-19 vaccine / Nur Qamarina Hamsa Hamsa, Nur Qamarina Analysis The Covid-19 virus has spread to all countries over the world. In order to handle and survived through this pandemic, a vaccine for Covid-19 was developed to give body a better immune system. However, many people has different point of view towards vaccine. People tend to share their opinions on social media which is Twitter platform such as the effectiveness and side effect of the vaccine. Goverment need to identify their sentiment in order to give better solution and actions related to Covid-19 vaccination. This project performed a sentiment analysis that identify people sentiment on Covid-19 vaccine. The data are collected through Twitter platform by collecting tweets discussing about Covid-19 vaccine and machine learning method was used to develop the sentiment model. The dataset areclean and processing by using natural language toolkit in Pyhton such as stopwords and NeatText library. The model used support vector machine classifier to classify the dataset into its polaritycategories and evaluate the accuracy. Performance metric such as precision, recall and F-score used to validate the model effectively. This project designed a dashboard to visualized overall information of sentiment analysis on Covid-19 vaccine. The dashboard was designed using dash plotly library in python. There are changes of people sentiment around vaccine over the time by monitoring the analysis and statistic provide in the dashboard visualization. This study improves understanding of the public opinion on Covid-19 vaccine. 2021-07 Thesis NonPeerReviewed text en https://ir.uitm.edu.my/id/eprint/59180/1/59180.pdf Sentiment analysis on Covid-19 vaccine / Nur Qamarina Hamsa. (2021) Degree thesis, thesis, Universiti Teknologi MARA, Perak. <http://terminalib.uitm.edu.my/59180.pdf>
institution Universiti Teknologi Mara
building Tun Abdul Razak Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Teknologi Mara
content_source UiTM Institutional Repository
url_provider http://ir.uitm.edu.my/
language English
topic Analysis
spellingShingle Analysis
Hamsa, Nur Qamarina
Sentiment analysis on Covid-19 vaccine / Nur Qamarina Hamsa
description The Covid-19 virus has spread to all countries over the world. In order to handle and survived through this pandemic, a vaccine for Covid-19 was developed to give body a better immune system. However, many people has different point of view towards vaccine. People tend to share their opinions on social media which is Twitter platform such as the effectiveness and side effect of the vaccine. Goverment need to identify their sentiment in order to give better solution and actions related to Covid-19 vaccination. This project performed a sentiment analysis that identify people sentiment on Covid-19 vaccine. The data are collected through Twitter platform by collecting tweets discussing about Covid-19 vaccine and machine learning method was used to develop the sentiment model. The dataset areclean and processing by using natural language toolkit in Pyhton such as stopwords and NeatText library. The model used support vector machine classifier to classify the dataset into its polaritycategories and evaluate the accuracy. Performance metric such as precision, recall and F-score used to validate the model effectively. This project designed a dashboard to visualized overall information of sentiment analysis on Covid-19 vaccine. The dashboard was designed using dash plotly library in python. There are changes of people sentiment around vaccine over the time by monitoring the analysis and statistic provide in the dashboard visualization. This study improves understanding of the public opinion on Covid-19 vaccine.
format Thesis
author Hamsa, Nur Qamarina
author_facet Hamsa, Nur Qamarina
author_sort Hamsa, Nur Qamarina
title Sentiment analysis on Covid-19 vaccine / Nur Qamarina Hamsa
title_short Sentiment analysis on Covid-19 vaccine / Nur Qamarina Hamsa
title_full Sentiment analysis on Covid-19 vaccine / Nur Qamarina Hamsa
title_fullStr Sentiment analysis on Covid-19 vaccine / Nur Qamarina Hamsa
title_full_unstemmed Sentiment analysis on Covid-19 vaccine / Nur Qamarina Hamsa
title_sort sentiment analysis on covid-19 vaccine / nur qamarina hamsa
publishDate 2021
url https://ir.uitm.edu.my/id/eprint/59180/1/59180.pdf
https://ir.uitm.edu.my/id/eprint/59180/
_version_ 1744357202757419008
score 13.211869

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