Detecting Fraud Apps using Sentiment Research
Mandava Rama Rao1, Nandhini Kannan2, CH V S Nihanth3
1Mandava Rama Rao, Department of Computer Science & Engineering, SRM Institute of Science and Technology, Chennai (Tamil Nadu), India.
2Nandhini Kannan, Department of Computer Science & Engineering, SRM Institute of Science and Technology, Chennai (Tamil Nadu), India.
3CH V S Nihanth, Department of Computer Science & Engineering, SRM Institute of Science and Technology, Chennai (Tamil Nadu), India.
Manuscript received on 19 July 2019 | Revised Manuscript received on 03 August 2019 | Manuscript Published on 10 August 2019 | PP: 580-584 | Volume-8 Issue-2S3 July 2019 | Retrieval Number: B11070782S319/2019©BEIESP | DOI: 10.35940/ijrte.B1107.0782S319
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: With the increase in the number of mobile applications in the day to day life, it is important to keep track as to which ones are safe and which ones aren’t. One can’t judge how safe and true each application is based only on the reviews that are mentioned for each application. Hence it is a need to keep track and develop a system to make sure the apps present are genuine or not. The objective is to develop a system in detecting fraud apps before the user downloads by using sentimental analysis and data mining. Sentimental analysis is to help in determining the emotional tones behind words which are expressed in online. This method is useful in monitoring social media and helps to get a brief idea of the public’s opinion on certain issues. The user cannot always get correct or true reviews about the product on the internet. We can check for user’s sentimental comments on multiple application. The reviews may be fake or genuine. Analyzing the rating and reviews together involving both user and admins comments, we can determine whether the app is genuine or not. Using sentimental analysis and data mining, the machine is able to learn and analyze the sentiments, emotions about reviews and other texts. The manipulation of review is one of the key aspects of App ranking fraud. By using sentimental analysis and data mining, analyzing reviews and comments can help to determine the correct application for both Android and iOSplatforms.
Keywords: Sentimental Analysis, Data Mining, Review based Evidence, Positive Negative Ratings, Rate Evidence, Users Review, Leading Session.
Scope of the Article: Data Mining