Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/162911
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dc.contributor.authorNur Lydia Afiqah Binte Rozalien_US
dc.date.accessioned2022-11-14T02:14:37Z-
dc.date.available2022-11-14T02:14:37Z-
dc.date.issued2022-
dc.identifier.citationNur Lydia Afiqah Binte Rozali (2022). A study on Covid-19 tweets. Final Year Project (FYP), Nanyang Technological University, Singapore. https://hdl.handle.net/10356/162911en_US
dc.identifier.urihttps://hdl.handle.net/10356/162911-
dc.description.abstractThe 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.en_US
dc.language.isoenen_US
dc.publisherNanyang Technological Universityen_US
dc.relationSCSE21-0717en_US
dc.subjectEngineering::Computer science and engineering::Dataen_US
dc.titleA study on Covid-19 tweetsen_US
dc.typeFinal Year Project (FYP)en_US
dc.contributor.supervisorSun Aixinen_US
dc.contributor.schoolSchool of Computer Science and Engineeringen_US
dc.description.degreeBachelor of Engineering (Computer Science)en_US
dc.contributor.supervisoremailAXSun@ntu.edu.sgen_US
item.grantfulltextrestricted-
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Appears in Collections:SCSE Student Reports (FYP/IA/PA/PI)
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