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TikNep: content analysis of Nepali TikTok users using natural language processing

dc.contributor.advisorSadeque, Farig Yousuf
dc.contributor.authorDhakal, Aakar
dc.contributor.authorLamichhane, Ashok
dc.contributor.authorJha, Aatish Kumar
dc.contributor.authorSingh, Mukund Prasad
dc.date.accessioned2024-10-17T06:06:54Z
dc.date.available2024-10-17T06:06:54Z
dc.date.copyright©2024
dc.date.issued2024-05
dc.identifier.otherID 20201203
dc.identifier.otherID 21201785
dc.identifier.otherID 20201206
dc.identifier.otherID 20201202
dc.identifier.urihttp://hdl.handle.net/10361/24343
dc.descriptionThis thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science, 2024.en_US
dc.descriptionCataloged from PDF version of thesis.
dc.descriptionIncludes bibliographical references (pages 49-52).
dc.description.abstractNepal, with an approximate population of 29 million, has over 2.2 million active TikTok users, TikTok has gained attention as a platform for self-expression and social connection among diverse age groups. Users in Nepal are using TikTok to share their opinions on matters related to politics, social issues, pop culture, lifestyle and beauty, sports, etc. While the content on platforms like Facebook and Twitter has been studied and evaluated thoroughly, the impact and influence of TikTok’s content on Nepali society have not been assessed yet. In this study, we propose to analyze content on Nepal’s TikTok using Natural Language Processing (NLP) tools to draw conclusions regarding where the conversation is being shifted towards. To meet this objective, we will focus on the comments posted by users on popular TikTok videos in Nepal and conduct Sentiment Analysis, Hate-Offense Detection, Political Stance Detection, and Multi-label Topic Classification.en_US
dc.description.statementofresponsibilityAakar Dhakal
dc.description.statementofresponsibilityAshok Lamichhane
dc.description.statementofresponsibilityAatish Kumar Jha
dc.description.statementofresponsibilityMukund Prasad Singh
dc.description.statementofresponsibilityAakar Dhakal
dc.description.statementofresponsibilityAshok Lamichhane
dc.description.statementofresponsibilityAatish Kumar Jha
dc.description.statementofresponsibilityMukund Prasad Singh
dc.format.extent62 pages
dc.language.isoenen_US
dc.publisherBrac Universityen_US
dc.rightsBrac University theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission.
dc.subjectNatural language processingen_US
dc.subjectContent analysisen_US
dc.subjectTikToken_US
dc.subjectSocial influenceen_US
dc.subjectSentiment analysisen_US
dc.subjectHate speechen_US
dc.subjectMulti-label topic classificationen_US
dc.subjectMachine learningen_US
dc.subject.lcshNatural language processing (Computer science).
dc.subject.lcshContent analysis (Communication)--Data processing.
dc.titleTikNep: content analysis of Nepali TikTok users using natural language processingen_US
dc.typeThesisen_US
dc.contributor.departmentDepartment of Computer Science and Engineering, Brac University
dc.description.degreeB.Sc. in Computer Science


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