Identifying code-mixed and code-switched hateful remarks on social media using NLP
This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science, 2024.
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Brac University
2024
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10361-242702024-10-01T21:02:04Z Identifying code-mixed and code-switched hateful remarks on social media using NLP Sinha, Sumaiya Nawar, Naharin Siddiqui Khan, Md. Abrar Faiaz Sadeque, Farig Rahman, Rafeed Department of Computer Science and Engineering, Brac University Cyberbullying Cyber harassment Online bullying Social media Hate speech NLP Natural language processing (Computer science). Automatic speech recognition. Deep learning (Machine learning). This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science, 2024. Cataloged from PDF version of thesis. Includes bibliographical references (pages 43-45). Online bullying has prevailed for years in the vast cesspool that is commonly known as the online social media. Increasing use of social media and online communication has led to a rise in cyberbullying– which is often facilitated by the abundant usage of code-mixing and code-switching. Research has been done to filter out these derogatory remarks. However, little research has been done on code-switched and code-mixed hateful remarks. English has blended into our Bangla language so effectively that people regularly use English letters to convey Bangla due to its convenience. English and Bangla are used interchangeably in regular conversations as well. Our main objective in this research is to detect these code-switched and code-mixed remarks– which we plan to do by taking advantage of the state-of-theart natural language processing technologies. Sumaiya Sinha Naharin Siddiqui Nawar Md. Abrar Faiaz Khan B.Sc. in Computer Science 2024-10-01T09:22:38Z 2024-10-01T09:22:38Z ©2024 2024-05 Thesis ID 20101141 ID 24141298 ID 19301106 http://hdl.handle.net/10361/24270 en Brac 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. 53 pages application/pdf Brac University |
| institution |
Brac University |
| collection |
Institutional Repository |
| language |
English |
| topic |
Cyberbullying Cyber harassment Online bullying Social media Hate speech NLP Natural language processing (Computer science). Automatic speech recognition. Deep learning (Machine learning). |
| spellingShingle |
Cyberbullying Cyber harassment Online bullying Social media Hate speech NLP Natural language processing (Computer science). Automatic speech recognition. Deep learning (Machine learning). Sinha, Sumaiya Nawar, Naharin Siddiqui Khan, Md. Abrar Faiaz Identifying code-mixed and code-switched hateful remarks on social media using NLP |
| description |
This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science, 2024. |
| author2 |
Sadeque, Farig |
| author_facet |
Sadeque, Farig Sinha, Sumaiya Nawar, Naharin Siddiqui Khan, Md. Abrar Faiaz |
| format |
Thesis |
| author |
Sinha, Sumaiya Nawar, Naharin Siddiqui Khan, Md. Abrar Faiaz |
| author_sort |
Sinha, Sumaiya |
| title |
Identifying code-mixed and code-switched hateful remarks on social media using NLP |
| title_short |
Identifying code-mixed and code-switched hateful remarks on social media using NLP |
| title_full |
Identifying code-mixed and code-switched hateful remarks on social media using NLP |
| title_fullStr |
Identifying code-mixed and code-switched hateful remarks on social media using NLP |
| title_full_unstemmed |
Identifying code-mixed and code-switched hateful remarks on social media using NLP |
| title_sort |
identifying code-mixed and code-switched hateful remarks on social media using nlp |
| publisher |
Brac University |
| publishDate |
2024 |
| url |
http://hdl.handle.net/10361/24270 |
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