Fake review detection using natural language processing (NLP) techniques
Detecting fake reviews is important for maintaining the authenticity and reliability of online platforms. In this project, we address the challenges of fake review detection using machine learning techniques, focusing on the application of DistilBERT model and adversarial sample generation. Our appr...
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| Format: | Final Year Project (FYP) |
| Language: | English |
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Nanyang Technological University
2024
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| Online Access: | https://hdl.handle.net/10356/176806 |
| _version_ | 1811678648914149376 |
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| author | Pyae Sone Khin |
| author2 | Lihui Chen |
| author_facet | Lihui Chen Pyae Sone Khin |
| author_sort | Pyae Sone Khin |
| collection | NTU |
| description | Detecting fake reviews is important for maintaining the authenticity and reliability of online platforms. In this project, we address the challenges of fake review detection using machine learning techniques, focusing on the application of DistilBERT model and adversarial sample generation. Our approach involves data preprocessing, which includes cleaning and augmentation, to ensure the quality and diversity of the dataset. This project used state-of-the-art technologies and modern tools to train and fine-tune the model and evaluate the performance in terms of precision, recall, F1-score, and accuracy.
This project highlights the significance of model training and evaluation methodologies to accurately detect between real and fake reviews. By combining adversarial samples into the training dataset, we enhance the model's resilience against manipulative inputs, ensuring its effectiveness in real-world scenarios. The outcomes of this project contribute to advancing fake review detection technologies, offering insights into leveraging machine learning for maintaining trust and credibility in online review systems. |
| first_indexed | 2024-10-01T02:56:37Z |
| format | Final Year Project (FYP) |
| id | ntu-10356/176806 |
| institution | Nanyang Technological University |
| language | English |
| last_indexed | 2024-10-01T02:56:37Z |
| publishDate | 2024 |
| publisher | Nanyang Technological University |
| record_format | dspace |
| spelling | ntu-10356/1768062024-05-24T15:43:14Z Fake review detection using natural language processing (NLP) techniques Pyae Sone Khin Lihui Chen School of Electrical and Electronic Engineering ELHCHEN@ntu.edu.sg Computer and Information Science Machine learning Fake review Adversarial attack Detecting fake reviews is important for maintaining the authenticity and reliability of online platforms. In this project, we address the challenges of fake review detection using machine learning techniques, focusing on the application of DistilBERT model and adversarial sample generation. Our approach involves data preprocessing, which includes cleaning and augmentation, to ensure the quality and diversity of the dataset. This project used state-of-the-art technologies and modern tools to train and fine-tune the model and evaluate the performance in terms of precision, recall, F1-score, and accuracy. This project highlights the significance of model training and evaluation methodologies to accurately detect between real and fake reviews. By combining adversarial samples into the training dataset, we enhance the model's resilience against manipulative inputs, ensuring its effectiveness in real-world scenarios. The outcomes of this project contribute to advancing fake review detection technologies, offering insights into leveraging machine learning for maintaining trust and credibility in online review systems. Bachelor's degree 2024-05-21T01:42:11Z 2024-05-21T01:42:11Z 2024 Final Year Project (FYP) Pyae Sone Khin (2024). Fake review detection using natural language processing (NLP) techniques. Final Year Project (FYP), Nanyang Technological University, Singapore. https://hdl.handle.net/10356/176806 https://hdl.handle.net/10356/176806 en A3030-231 application/pdf Nanyang Technological University |
| spellingShingle | Computer and Information Science Machine learning Fake review Adversarial attack Pyae Sone Khin Fake review detection using natural language processing (NLP) techniques |
| title | Fake review detection using natural language processing (NLP) techniques |
| title_full | Fake review detection using natural language processing (NLP) techniques |
| title_fullStr | Fake review detection using natural language processing (NLP) techniques |
| title_full_unstemmed | Fake review detection using natural language processing (NLP) techniques |
| title_short | Fake review detection using natural language processing (NLP) techniques |
| title_sort | fake review detection using natural language processing nlp techniques |
| topic | Computer and Information Science Machine learning Fake review Adversarial attack |
| url | https://hdl.handle.net/10356/176806 |
| work_keys_str_mv | AT pyaesonekhin fakereviewdetectionusingnaturallanguageprocessingnlptechniques |