Sadeque, Farig YousufDhakal, AakarLamichhane, AshokJha, Aatish KumarSingh, Mukund Prasad2024-10-172024-10-17©20242024-05ID 20201203ID 21201785ID 20201206ID 20201202http://hdl.handle.net/10361/24343Cataloged from PDF version of thesis.Includes bibliographical references (pages 49-52).This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science, 2024.Nepal, 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.62 pagesenBrac 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.Natural language processingContent analysisTikTokSocial influenceSentiment analysisHate speechMulti-label topic classificationMachine learningNatural language processing (Computer science).Content analysis (Communication)--Data processing.Thesis