A study on Covid-19 tweets

The spread of infectious diseases has caused economic and human losses throughout history. The outbreak of the COVID-19 virus changed the lives of people around the world. Social media, such as Twitter, have played a significant role in providing the general public with the latest information and...

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Main Author: Nur Lydia Afiqah Binte Rozali
Other Authors: Sun Aixin
Format: Final Year Project
Language:English
Published: Nanyang Technological University 2022
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Online Access:https://hdl.handle.net/10356/162911
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Institution: Nanyang Technological University
Language: English
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spelling sg-ntu-dr.10356-1629112022-11-14T02:14:38Z A study on Covid-19 tweets Nur Lydia Afiqah Binte Rozali Sun Aixin School of Computer Science and Engineering AXSun@ntu.edu.sg Engineering::Computer science and engineering::Data The spread of infectious diseases has caused economic and human losses throughout history. The outbreak of the COVID-19 virus changed the lives of people around the world. Social media, such as Twitter, have played a significant role in providing the general public with the latest information and policy updates related to COVID-19 throughout the pandemic and government bodies [3]. Twitter is a platform for users to express their opinions and views. With the help of this microblogging platform, data can be extracted that can be used for sentiment and emotional analysis, a technique that is referred to as natural language processing (NLP). Over 14 months from 1 February 2020 to 31 March 2021, two billion multilingual tweets related to the COVID-19 pandemic were extracted and analyzed in a previous study [5]. This study will explore the data collection of tweets collected for COVID-19 from TBCOV [5]. The focus will be on the evolution of COVID-19 and understanding the trends of sentiments posted by Twitter users throughout South-East Asia, with a centering on Singapore, Thailand, Myanmar, and Vietnam during the COVID-19 pandemic. The results of the most indicative terms and named entities will be discussed using the Relative Entropy formula. Bachelor of Engineering (Computer Science) 2022-11-14T02:14:37Z 2022-11-14T02:14:37Z 2022 Final Year Project (FYP) Nur Lydia Afiqah Binte Rozali (2022). A study on Covid-19 tweets. Final Year Project (FYP), Nanyang Technological University, Singapore. https://hdl.handle.net/10356/162911 https://hdl.handle.net/10356/162911 en SCSE21-0717 application/pdf Nanyang Technological University
institution Nanyang Technological University
building NTU Library
continent Asia
country Singapore
Singapore
content_provider NTU Library
collection DR-NTU
language English
topic Engineering::Computer science and engineering::Data
spellingShingle Engineering::Computer science and engineering::Data
Nur Lydia Afiqah Binte Rozali
A study on Covid-19 tweets
description The spread of infectious diseases has caused economic and human losses throughout history. The outbreak of the COVID-19 virus changed the lives of people around the world. Social media, such as Twitter, have played a significant role in providing the general public with the latest information and policy updates related to COVID-19 throughout the pandemic and government bodies [3]. Twitter is a platform for users to express their opinions and views. With the help of this microblogging platform, data can be extracted that can be used for sentiment and emotional analysis, a technique that is referred to as natural language processing (NLP). Over 14 months from 1 February 2020 to 31 March 2021, two billion multilingual tweets related to the COVID-19 pandemic were extracted and analyzed in a previous study [5]. This study will explore the data collection of tweets collected for COVID-19 from TBCOV [5]. The focus will be on the evolution of COVID-19 and understanding the trends of sentiments posted by Twitter users throughout South-East Asia, with a centering on Singapore, Thailand, Myanmar, and Vietnam during the COVID-19 pandemic. The results of the most indicative terms and named entities will be discussed using the Relative Entropy formula.
author2 Sun Aixin
author_facet Sun Aixin
Nur Lydia Afiqah Binte Rozali
format Final Year Project
author Nur Lydia Afiqah Binte Rozali
author_sort Nur Lydia Afiqah Binte Rozali
title A study on Covid-19 tweets
title_short A study on Covid-19 tweets
title_full A study on Covid-19 tweets
title_fullStr A study on Covid-19 tweets
title_full_unstemmed A study on Covid-19 tweets
title_sort study on covid-19 tweets
publisher Nanyang Technological University
publishDate 2022
url https://hdl.handle.net/10356/162911
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