Identifying hate speech of Bangla language text using natural language processing
This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering, 2024.
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| Idioma: | English |
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Brac University
2024
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| Acesso em linha: | http://hdl.handle.net/10361/22864 |
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10361-228642024-05-19T21:05:32Z Identifying hate speech of Bangla language text using natural language processing Rahman, Mushfiqur Jui, Razia Sultana Sakib, Chowdhury Nazmuz Ridoy, Fahim Alavi Ananya, Taskiea Tabassum Rasel, Annajiat Alim Hossain, Muhammad Iqbal Karim, Dewan Ziaul Department of Computer Science and Engineering, Brac University Bangla language Natural language processing Machine learning Deep learning Offensive language 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 and Engineering, 2024. Cataloged from PDF version of thesis. Includes bibliographical references (pages 22-24). In this era of the internet, sharing information through social media has provided significant benefits to humans. People can easily access and observe others’ lifestyles and work, as well as make comments or share thoughts about them. However, this practice also brings challenges, such as the spread of hate comments, abusive online criticism, spreading toxicity by giving hate comments etc. The internet’s flexibility and anonymity have created a culture where users find it easy to express themselves aggressively in communication. As the amount of hate speech is increasing, there is a need for a method to automatically detect hate speech. To tackle this concern, recent research has utilized diverse feature engineering methods and machine learning algorithms to autonomously identify hate speech messages across various datasets.Since it is related to Natural Language Processing (NLP), our goal is to utilize NLP to detect hate speeches and demonstrate how Deep Learning and ML can be used in this case.. Since there are more than 7,100 languages spoken throughout the world, we have chosen the Bengali language as our dataset language. Additionally, with the help of machine learning and deep learning, we will train our model to automatically detect hate speech. We are utilizing Multinomial Naive Bayes, RNN, Random Forest, Logistic Regression, Decision Tree Classifier, CNN-LSTM Hybrid algorithm and Multi lingual Bidirectional Encoder Representations(mBert) for result comparison and optimal outcomes and accuracy. After employing all the above algorithms, we found the highest accuracy using the mBert for the binary classification, which is 90.00%. On the other hand, for multiclass classifications, we have found the highest accuracy using CNN-LSTM Hybrid algorithm, which is 64% and the second highest is 62% using mBert. We are committed to further improving these results. Mushfiqur Rahman Razia Sultana Jui Chowdhury Nazmuz Sakib Fahim Alavi Ridoy Taskiea Tabassum Ananya B.Sc in Computer Science and Engineering 2024-05-19T06:21:47Z 2024-05-19T06:21:47Z ©2024 2024-01 Thesis ID: 18301121 ID: 18301021 ID: 18301109 ID: 19301071 ID: 19301192 http://hdl.handle.net/10361/22864 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. 34 pages application/pdf Brac University |
| institution |
Brac University |
| collection |
Institutional Repository |
| language |
English |
| topic |
Bangla language Natural language processing Machine learning Deep learning Offensive language Natural language processing (Computer science) Automatic speech recognition Deep learning (Machine learning) |
| spellingShingle |
Bangla language Natural language processing Machine learning Deep learning Offensive language Natural language processing (Computer science) Automatic speech recognition Deep learning (Machine learning) Rahman, Mushfiqur Jui, Razia Sultana Sakib, Chowdhury Nazmuz Ridoy, Fahim Alavi Ananya, Taskiea Tabassum Identifying hate speech of Bangla language text using natural language processing |
| description |
This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering, 2024. |
| author2 |
Rasel, Annajiat Alim |
| author_facet |
Rasel, Annajiat Alim Rahman, Mushfiqur Jui, Razia Sultana Sakib, Chowdhury Nazmuz Ridoy, Fahim Alavi Ananya, Taskiea Tabassum |
| format |
Thesis |
| author |
Rahman, Mushfiqur Jui, Razia Sultana Sakib, Chowdhury Nazmuz Ridoy, Fahim Alavi Ananya, Taskiea Tabassum |
| author_sort |
Rahman, Mushfiqur |
| title |
Identifying hate speech of Bangla language text using natural language processing |
| title_short |
Identifying hate speech of Bangla language text using natural language processing |
| title_full |
Identifying hate speech of Bangla language text using natural language processing |
| title_fullStr |
Identifying hate speech of Bangla language text using natural language processing |
| title_full_unstemmed |
Identifying hate speech of Bangla language text using natural language processing |
| title_sort |
identifying hate speech of bangla language text using natural language processing |
| publisher |
Brac University |
| publishDate |
2024 |
| url |
http://hdl.handle.net/10361/22864 |
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