SayamAlt/Fake-Reviews-Detection
Successfully developed a machine learning model which can predict whether an online review is fraudulent or not. The main idea used to detect the fake nature of reviews is that the review should be computer generated through unfair means. If the review is created manually, then it is considered legal and original.
This helps e-commerce managers and brand strategists identify fraudulent product reviews. It takes in a collection of online reviews, each with text, category, and a rating, and determines if they are computer-generated fakes or genuine human-created feedback. The output clearly labels which reviews are trustworthy and which are not, helping maintain brand integrity and accurate product perception.
102 stars. No commits in the last 6 months.
Use this if you need to filter through large volumes of online product reviews to distinguish between authentic customer feedback and artificially generated content.
Not ideal if you're trying to detect fake reviews based on sentiment manipulation or human-generated but malicious content, as it focuses specifically on computer-generated text.
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Apr 14, 2022
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