A conventional & deep learning strategy for analyzing & detecting Bengali fake news in online medium
This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering, 2023.
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| Լեզու: | English |
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Brac University
2023
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| Առցանց հասանելիություն: | http://hdl.handle.net/10361/21171 |
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10361-211712023-09-24T21:11:22Z A conventional & deep learning strategy for analyzing & detecting Bengali fake news in online medium Ahmed, Istiak Prima, Shanzida Binta Akram Baptee, Tahsin Anzum Afroz, Mehrin Shanto, Ariful Islam Rasel, Annajiat Alim Sadeque, Farig Yousuf Department of Computer Science and Engineering, Brac University Conventional machine learning models Deep learning models Classic machine learning algorithms Feed-forward neural networks Recurrent Neural Networks (RNN) Machine learning Cognitive learning theory Neural networks (Computer science) This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering, 2023. Cataloged from PDF version of thesis. Includes bibliographical references (pages 29-31). Nowadays, social networking sites like Facebook and Twitter have become an sig- nificant impact on our lives . We use such sites to remain in touch with one another and as a source of news to stay informed about current events. As a result, we frequently see news articles with click-bait headlines from various web portals that lack authenticity. The majority of these sites that share these sorts of links are used to manipulate people and spread false propaganda. We intended to utilize both traditional machine learning algorithms and deep learning algorithms on manually annotated data-sets to create effective approaches for spotting Bangla fake news on online media that included about 8,500 pieces of news data. In particular, in this project, we used classic machine learning algorithms for text classification such as “Naive Bayes Classifier”, “Support Vector Machines (SVM)”, “K-Nearest Neigh- bor (KNN)” as well as other classification-based algorithms such as “Decision Tree (DT)”, “Logistic Regression (LR)”, “Random Forest” and “AdaBoost”. We have also used deep learning models based on Feed-Forward Neural Networks such as “Convolutional Neural Network (CNN)” as well as a variety of Recurrent Neural Networks (RNN) such as “Long-Short Term Memory (LSTM)”, “Gated Recurrent Unit (GRU)” to detect fake news on online media. To conclude, our research focused on developing precise strategies for spotting fake news on social media sites. Istiak Ahmed Shanzida Binta Akram Prima Tahsin Anzum Baptee Mehrin Afroz Ariful Islam Shanto B. Computer Science and Engineering 2023-09-24T05:43:06Z 2023-09-24T05:43:06Z 2023 2023-04 Thesis ID 21241066 ID 19101174 ID 22141041 ID 21241078 ID 19101369 http://hdl.handle.net/10361/21171 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. 31 pages application/pdf Brac University |
| institution |
Brac University |
| collection |
Institutional Repository |
| language |
English |
| topic |
Conventional machine learning models Deep learning models Classic machine learning algorithms Feed-forward neural networks Recurrent Neural Networks (RNN) Machine learning Cognitive learning theory Neural networks (Computer science) |
| spellingShingle |
Conventional machine learning models Deep learning models Classic machine learning algorithms Feed-forward neural networks Recurrent Neural Networks (RNN) Machine learning Cognitive learning theory Neural networks (Computer science) Ahmed, Istiak Prima, Shanzida Binta Akram Baptee, Tahsin Anzum Afroz, Mehrin Shanto, Ariful Islam A conventional & deep learning strategy for analyzing & detecting Bengali fake news in online medium |
| description |
This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering, 2023. |
| author2 |
Rasel, Annajiat Alim |
| author_facet |
Rasel, Annajiat Alim Ahmed, Istiak Prima, Shanzida Binta Akram Baptee, Tahsin Anzum Afroz, Mehrin Shanto, Ariful Islam |
| format |
Thesis |
| author |
Ahmed, Istiak Prima, Shanzida Binta Akram Baptee, Tahsin Anzum Afroz, Mehrin Shanto, Ariful Islam |
| author_sort |
Ahmed, Istiak |
| title |
A conventional & deep learning strategy for analyzing & detecting Bengali fake news in online medium |
| title_short |
A conventional & deep learning strategy for analyzing & detecting Bengali fake news in online medium |
| title_full |
A conventional & deep learning strategy for analyzing & detecting Bengali fake news in online medium |
| title_fullStr |
A conventional & deep learning strategy for analyzing & detecting Bengali fake news in online medium |
| title_full_unstemmed |
A conventional & deep learning strategy for analyzing & detecting Bengali fake news in online medium |
| title_sort |
conventional & deep learning strategy for analyzing & detecting bengali fake news in online medium |
| publisher |
Brac University |
| publishDate |
2023 |
| url |
http://hdl.handle.net/10361/21171 |
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