Fraud Apps Detection Using Sentiment Analysis and Spam Filtering

Fraud Apps Detection Using Sentiment Analysis and Spam Filtering

Aditya Gurav1 Shankar Channe2 Rohan Chavav3 Anmesh guldagad4

under the guidance of Prof. Mayuri Vengurlekar

1-3Computer Engineering, K J College of Engineering and Management Research, Pune, India

Abstract— in the mobile app industry, ranking fraud is the practise of engaging in dishonest or deceitful behaviour with the intention of artificially boosting an App's position on a popularity list. In fact, ranking fraud by app developers is becoming more and more common. These practises include inflating their apps' sales or uploading fake app reviews. Although the significance of preventing ranking fraud has long been understood, little knowledge and research have been done in this field. In order to do this, we present a comprehensive analysis of fraud app detection using sentiment analysis and spam filtering in this study and suggest a system for detecting it in mobile apps. We specifically suggest mining the active times, or leading sessions, of mobile Apps to precisely locate the ranking scam in the first place.

Keywords- Mobile Apps, Fraud Detection, Rating and Review, sentiment analysis, spam filtering.