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

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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.issued2024-05
dc.descriptionCataloged from PDF version of thesis.
dc.descriptionIncludes bibliographical references (pages 49-52).
dc.descriptionThis thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science, 2024.
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.
dc.identifier.otherID 20201203
dc.identifier.otherID 21201785
dc.identifier.otherID 20201206
dc.identifier.otherID 20201202
dc.identifier.otherhttps://dspace.bracu.ac.bd/server/api/core/items/2d86266d-6b27-4c3a-bc17-f7a435e4c8f7
dc.identifier.urihttp://hdl.handle.net/10361/24343
dc.language.isoen
dc.publisherBRAC University
dc.sourceBRAC University Institutional Repository
dc.subjectNatural language processing
dc.subjectContent analysis
dc.subjectTikTok
dc.subjectSocial influence
dc.subjectSentiment analysis
dc.subjectHate speech
dc.subjectMulti-label topic classification
dc.subjectMachine learning
dc.titleTikNep: content analysis of Nepali TikTok users using natural language processing
dc.typeThesis

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Thesis (Bachelor of Science in Computer Science)