Review - Rating mismatch detection using sentiment analysis on App store

Abstract

" Machine learning is a subset of artificial intelligence (AI) that allows computers to learn and develop on their own despite having to be specifically configured, and also it is concerned with the development of computer programs that can access data and learn on their own withoutthe need for user interaction. Deep learning also could be viewed as a subset of machine learning. This is an area that is focused on computer algorithms learning and developing on their own. Deep learning uses artificial neural networks, which are programmed to replicate how humans think and learn, as opposed to machine learning, which uses simpler concepts. This project aims to detect mismatch between user review and rating on the App Store using machine learning and deep learning. Application user reviews and ratings have a major impact on a new user’s decision to download or not download the app. Most of the time, end users post a bad comment and give Reviews and ratings are kind of an advertisement for an app and these reviews always help consumers to make their decision. From the app developer side, reviews and ratings can have a high impact on app store optimization and app store ranking. In this kind of situation these reviews, and ratings can be fake or false purposely or not. In this research, the researcher is going to detect mismatch between review and ratings of applications in the app store. This will help to calculate more correct and actual rating value for an app."