Authenticated User Reviews Based on Genuine Ratings for Apps

9 Pages Posted: 27 Apr 2018

See all articles by Samakoti Tejasree

Samakoti Tejasree

Vellore Institute of Technology (VIT), Vellore, School of Computer Science and Engineering, Students

Tella Prameela

Sri Venkateswara College of Engineering (SVCE) - Department of Computer Science and Engineering

Jasmine Sabeena

Sri Venkateswara Engineering College for Women (SVEW) - Department of Computer Science and Engineering

Shaik Naseera

Vellore Institute of Technology (VIT) - School of Computer Science and Engineering

Date Written: February 7, 2018

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. Due to this an app user has no facility to express her views. Even though the same technique in ratings also. It becomes more and more frequent for app developers to increase the spreading of their apps sales or app ratings to commit ranking fraud. Mainly providing a view of reviews impact on the mobile apps or products and also detects the fake reviews list by the users. There are mainly three evidences to become aware of the fraud in the mobile apps, i.e., ranking based evidences, rating based evidences and finally review based evidences. Compare to remaining two evidences review based evidences are most helpful to the users who are trying to download new apps. Here the main concern is authenticated users reviews means that the users who have already have an account in that field. And review based evidences are plays very crucial. Accurately locate the ranking fraud by mining active periods namely leading sessions for mobile apps. And also discuss how the reviews are to be most useful for the new clients.

Keywords: Mobile Apps, Review of apps, fake reviews, Privacy

Suggested Citation

Tejasree, Samakoti and Prameela, Tella and Sabeena, Jasmine and Naseera, Shaik, Authenticated User Reviews Based on Genuine Ratings for Apps (February 7, 2018). 2018 IADS International Conference on Computing, Communications & Data Engineering (CCODE) 7-8 February, Available at SSRN: https://ssrn.com/abstract=3168416 or http://dx.doi.org/10.2139/ssrn.3168416

Samakoti Tejasree (Contact Author)

Vellore Institute of Technology (VIT), Vellore, School of Computer Science and Engineering, Students ( email )

Vellore, Tamil Nadu
India

Tella Prameela

Sri Venkateswara College of Engineering (SVCE) - Department of Computer Science and Engineering

Sriperumbudur
Tamil Nadu
Pennalur, Sriperumbudur 602105
India

Jasmine Sabeena

Sri Venkateswara Engineering College for Women (SVEW) - Department of Computer Science and Engineering ( email )

Mangalam
Tirupati, Andhra Pradesh 517507
India

Shaik Naseera

Vellore Institute of Technology (VIT) - School of Computer Science and Engineering ( email )

Vellore, TN Tamil Nadu 632014
India

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