Vulgar and spam comment identification using Gluon Natural Language Processing and Convolution Neural Networks
This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering, 2019.
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| Jezik: | English |
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BRAC University
2019
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| Online pristup: | http://hdl.handle.net/10361/12267 |
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10361-122672022-01-26T10:20:05Z Vulgar and spam comment identification using Gluon Natural Language Processing and Convolution Neural Networks Jahan, Rufyda Mobin, Iftekharul Department of Computer Science and Engineering, Brac University Comment classification CNN Natural language processing Natural language processing (Computer science). This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering, 2019. Cataloged from PDF version of thesis. Includes bibliographical references (page 32). With the advancement of technology, the virtual platform and social media have become an important part of people’s daily life. The social media allows users to communicate, to express their feelings and to discuss on various topics. But cyber bullying and vulgar or toxic comments become an alarming problem in social media. In this paper, a system has been proposed to detect and classify vulgar comments using convolutional neural networking with gluon natural language processing. The system can classify toxic, hate speech, insult, obscene, threat and normal text by training from a huge dataset obtained from Kaggle, extracting comments from YouTube, facebook through extension of browser. The system shows 95.4% accuracy to detect and classify the vulgar comments. Jahan, Rufyda Rufyda Jahan B. Computer Science and Engineering 2019-06-27T10:43:49Z 2019-06-27T10:43:49Z 2019 2019-04 Thesis ID 13201077 http://hdl.handle.net/10361/12267 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. 32 pages application/pdf BRAC University |
| institution |
Brac University |
| collection |
Institutional Repository |
| language |
English |
| topic |
Comment classification CNN Natural language processing Natural language processing (Computer science). |
| spellingShingle |
Comment classification CNN Natural language processing Natural language processing (Computer science). Jahan, Rufyda Vulgar and spam comment identification using Gluon Natural Language Processing and Convolution Neural Networks |
| description |
This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering, 2019. |
| author2 |
Mobin, Iftekharul |
| author_facet |
Mobin, Iftekharul Jahan, Rufyda |
| format |
Thesis |
| author |
Jahan, Rufyda |
| author_sort |
Jahan, Rufyda |
| title |
Vulgar and spam comment identification using Gluon Natural Language Processing and Convolution Neural Networks |
| title_short |
Vulgar and spam comment identification using Gluon Natural Language Processing and Convolution Neural Networks |
| title_full |
Vulgar and spam comment identification using Gluon Natural Language Processing and Convolution Neural Networks |
| title_fullStr |
Vulgar and spam comment identification using Gluon Natural Language Processing and Convolution Neural Networks |
| title_full_unstemmed |
Vulgar and spam comment identification using Gluon Natural Language Processing and Convolution Neural Networks |
| title_sort |
vulgar and spam comment identification using gluon natural language processing and convolution neural networks |
| publisher |
BRAC University |
| publishDate |
2019 |
| url |
http://hdl.handle.net/10361/12267 |
| work_keys_str_mv |
AT jahanrufyda vulgarandspamcommentidentificationusinggluonnaturallanguageprocessingandconvolutionneuralnetworks |
| _version_ |
1814309192597504000 |