Detecting Fraud Apps Using Sentiment Analysis

Download Project Document/Synopsis

Most of us use android and IOS Mobiles these days and also uses the play store or app store capability normally. Both the stores provide great number of application but unluckily few of those applications are fraud. Such applications dose damage to phone and also may be data thefts. Hence, such applications must be marked, so that they will be identifiable for store users. So we are proposing a web application which will process the information, comments and the review of the application. So it will be easier to decide which application is fraud or not. Multiple application can be processed at a time with the web application. Also User cannot always get correct or true reviews about the product on internet. So rating/comments will be judged by the admin and it would be easy for admin to predict the application as Genuine or Fraud.

  • The proposed framework is scalable and can be extended with other domain generated evidences for ranking fraud detection.
  • Experimental results show the effectiveness of the proposed system, the scalability of the detection algorithm as well as some regularity of ranking fraud activities.
  • To the best of our knowledge, them is no existing benchmark to decide which leading sessions or Apps really contain ranking fraud. Thus, we develop four intuitive baselines and invite five human evaluators to validate.
  • Requires active internet connection.
  • System may provide inaccurate results if data entered incorrectly.

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