Genuine ratings for mobile apps with the support of authenticated users’ reviews

Abstract

Ranking fraud on the mobile app market refers liable to mislead activities which have a purpose of bumping up the apps in popularity list. Because of this, app users have no facility to express their views. This is the same technique in ratings also. It ends up bringing increasing number of visits for application engineers to build the spreading of their application deals or application appraisals to submit the positioning extortion. It mainly provides a view of reviews to impact on the mobile apps or products and also detects the fake review list by the users. There are mainly three evidences to end up plainly mindful of the fraud in the mobile apps, i.e., positioning-based confirmations, rating-based confirmations, and finally review-based evidences. Compared to the remaining two evidences, review-based evidences are most helpful to the users who are trying to download new apps. Here, the main concern is the reviews of the authenticated users, that is, the users who already have an account in that field. And review-based evidences are very crucial. We precisely find the positioning extortion by mining dynamic periods in particular driving sessions for mobile apps and also discuss how the reviews are most useful for the new clients.