Project Title: Identifying Fake Product Reviews Using Opinion Mining
Category: Information Mining and Retrieval
Project File: Download Project File
Tayyaba Sehar
Tayyaba.sehar@vu.edu.pk
Tayyaba.sehar13@outlook.com
Identifying Fake Product Reviews Using Opinion Mining
Project Domain / Category:
NLP/Information Retrieval
Abstract / Introduction:
As most of the people require review about a product before spending their money on the product. So people come across various reviews in the website but these reviews are genuine or fake is not identified by the user. In some review websites some good reviews are added by the product company people itself in order to make product famous this people belong to Social Media Optimization team. They give good reviews for many different products manufactured by their own firm. User will not be able to find out whether the review is genuine or fake. To find out fake review in the website this “Identifying Fake Product Reviews Using Opinion Mining” system will be developed. This system will find out fake reviews made by the social media optimization team by identifying the IP address. User will login to the system using his user id and password and will view various products and will give review about the product. To find out the review is fake or genuine, system will find out the IP address of the user if the system observe fake review send by the same IP Address many at times it will inform the admin to remove that review from the system. Once the fake reviews removed, the system will rate and rank the opinions on different products by using opinion mining techniques. This system helps the user to find out correct review of the product.
Functional Requirements:
1. The system should be able to add products to the system.
2. The system should be able to delete the review which is fake.
3. The system should be able to allow user once to access the system, user can view product and can post review about the product.
4. The system should be able to track the IP address of the user.
5. If the system observes fake review coming from same IP address many a times, then system should be able to track this IP address and will inform the admin to remove this review from the system.
❖ Modules:
The system comprises of 2 major modules with their sub-modules as follows:
1. Admin Login: Admin login to the system using his admin ID and password.
• Add product:
- Admin will add product to the system.
• Store Review for detection of Fake Reviews:
The system should store each review along with associated metadata, such as:
- User ID
- Timestamp
- Product ID
- IP Address (for tracking)
• Delete Review:
- Admin will remove the review which tracked by the system as fake.
• Review Monitoring (Opinion Mining):
Once the system detect/remove the fake reviews. The system should analyze each submitted review on the products using opinion mining (text analysis) techniques and rank the product according to their sentiments score. This includes:
o Sentiment Analysis: To detect whether the review is positive, negative, or neutral.
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2. User Login: User will login to the system using his user ID and password.
• View product:
- User will view product.
• Post Review:
- User can post review about the product.
Tools:
• Python/Visual Studio
• Senti WordNet Dictionary/Vader
• WAMP Server
• My SQL 5.6
• Apache/Nginx (Server-side to capture IP addresses)
• Notepad++
Supervisor:
Name: Tayyaba Sehar
Email ID: tayyaba.sehar@vu.edu.pk
Skype ID: Tayyaba.sehar13@outlook.com
Reviewer: Ahmad
Submitted on: Wednesday 9, April, 2025 10:39PM
Supervisor Behavior: Serious & Strict
Supervisor asks many questions, wants clear and correct answers, doesn’t help much.
Review:
Ye wo supervisor h Jo kehti h k line no 18 sa 24 tk Jo code likha h esa remove kro or mere samnay yhi code dubara likho mean shi judge krti g samnay walay ko kitni knowledge h ye comments on logo k thy Jo viva in ko da chukay thy.