TO FIND OUT THE FLAWS IN A PRODUCT FROM USER COMMENTS AGAINST UPLOADED VIDEO OF A PRODUCT

Abstract

Opinion mining is used to automatize the observation of subjective information like opinions and attitudes, and emotions, and feelings. The goal of this project is to find out the flaws in a product from user comments against uploaded video ofa product. In this project we use YouTube as platform to get a user comment from there. The reason to select YouTube is because they have more user than others. More the data, the more chances to reach out the goal which we set. To develop a system where end-user can upload the links ofYouTube video and get out the sentiment ofuser who comment on video. We use PYTHON as a programming language and the platform ANACONDA. We use Google API to extract the YouTube comments from videos in a very large quantity. As we said above, the more data, the more chances to get a better accuracy. In this project we gather 30000 comments with tagging manually for test data. i ! This report explore a technique use to achieve our objective. Different stages involve to export YouTube comment using Google API, manually tagging, data cleaning, pre processing, applying a text mining algorithm and then output a Result in a bar chart which shows how many people like the specific specification of a particular product. In this project, we used the iPhone model X PRO as a product