Sarvaiya, Jinal Jaisukh (2022) Multilingual Text Analysis using Natural Language Processing and Transfer Learning. Masters thesis, Dublin, National College of Ireland.
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Abstract
It only takes one toxic comment to sour the debate of internet. Trust and safety teams at major social media companies face this difficulty of examining the behaviour and activities such as online chats. Different lexicons and languages are used to make up range of settings which contains words or phrases of these exchanges. If these toxic comments and contributions to social media or web are identified, then we would have a much safer and more interactive contributions to internet. By using Natural Language Processing and Transfer Learning, we experiment by expansion of modelling capabilities with intentions of identifying toxicity on online comments and promoting trust and safety of the user. We'll examine the accuracies of several models, such as BERT and others, and derive insights into the effectiveness of pre-trained language models on categorizing multilingual text versus traditional methods. To help assist in the industry multilingual and multi-label classification model are developed which will help to assist industry in knowing its worth by various tactics.
Item Type: | Thesis (Masters) |
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Subjects: | Q Science > QA Mathematics > Electronic computers. Computer science T Technology > T Technology (General) > Information Technology > Electronic computers. Computer science P Language and Literature > P Philology. Linguistics > Computational linguistics. Natural language processing Z Bibliography. Library Science. Information Resources > ZA Information resources > ZA4150 Computer Network Resources > The Internet > World Wide Web > Websites > Online social networks T Technology > TK Electrical engineering. Electronics. Nuclear engineering > Telecommunications > The Internet > World Wide Web > Websites > Online social networks |
Divisions: | School of Computing > Master of Science in Data Analytics |
Depositing User: | Tamara Malone |
Date Deposited: | 10 Mar 2023 16:42 |
Last Modified: | 10 Mar 2023 16:42 |
URI: | https://norma.ncirl.ie/id/eprint/6293 |
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