Open AccessIdentification of Fraud Apps Using Sentiment Analysis Techniques
Author(s) -
Abeer Aljumah,
Amjad Altuwijri,
Thekra Alsuhaibani,
Afef Selmi,
Nada Alruhaily
Publication year - 2021
Publication title -
international journal of interactive mobile technologies
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.316
H-Index - 16
ISSN - 1865-7923
DOI - 10.3991/ijim.v15i23.27361
Subject(s) - computer science , sentiment analysis , feeling , identification (biology) , internet privacy , mobile apps , biometrics , android (operating system) , filter (signal processing) , task (project management) , world wide web , password , computer security , data science , human–computer interaction , artificial intelligence , psychology , engineering , social psychology , botany , computer vision , biology , operating system , systems engineering
Considering that application’s security is an important aspect, especially nowadays with the increase in technology and the number of fraudsters. It should be noted that determining the security of an application is a difficult task, especially since most fraudsters have become skilled and professional at manipulating people and stealing their sensitive data. Therefore, we pay attention to spot insecure apps by analyzing user feedback on Google Play platform using sentiment analysis. As it is known, user reviews reflect their experiments and experiences in addition to their feelings and satisfaction with the application. But unfortunately, not all of these reviews are real, fake reviews do not reflect the sincerity of feelings, so we have been keen in our work to filter the reviews and deliver accurate and correct results. This tool is useful for both users wanting to install an android app and for developers interested in app’s optimization.