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Google Play Content Scraping and Knowledge Engineering using Natural Language Processing Techniques with the Analysis of User Reviews

Authors
  • Aldabbas, Hamza1
  • Bajahzar, Abdullah2
  • Alruily, Meshrif3
  • Qureshi, Ali Adil4
  • Amir Latif, Rana M.5
  • Farhan, Muhammad5
  • 1 Prince Abdullah bin Ghazi Faculty of Information and Communication Technology, Al-Balqa Applied University, Jordan , (Jordan)
  • 2 Department of Computer Science and Information, College of Science at Zulfi, Majmaah University, 11932 , (Saudi Arabia)
  • 3 Faculty of Computer and information sciences, Jouf University, Saudi Arabia , (Saudi Arabia)
  • 4 Department of Computer Science Khawaja Fareed University of Engineering and Information Technology, Pakistan , (Pakistan)
  • 5 Department of Computer Science COMSATS University Islamabad, Sahiwal Campus , (Pakistan)
Type
Published Article
Journal
Journal of Intelligent Systems
Publisher
De Gruyter
Publication Date
Jul 17, 2020
Volume
30
Issue
1
Pages
192–208
Identifiers
DOI: 10.1515/jisys-2019-0197
Source
De Gruyter
Keywords
License
Green

Abstract

To maintain the competitive edge and evaluating the needs of the quality app is in the mobile application market. The user’s feedback on these applications plays an essential role in the mobile application development industry. The rapid growth of web technology gave people an opportunity to interact and express their review, rate and share their feedback about applications. In this paper we have scrapped 506259 of user reviews and applications rate from Google Play Store from 14 different categories. The statistical information was measured in the results using different of common machine learning algorithms such as the Logistic Regression, Random Forest Classifier, and Multinomial Naïve Bayes. Different parameters including the accuracy, precision, recall, and F1 score were used to evaluate Bigram, Trigram, and N-gram, and the statistical result of these algorithms was compared. The analysis of each algorithm, one by one, is performed, and the result has been evaluated. It is concluded that logistic regression is the best algorithm for review analysis of the Google Play Store applications. The results have been checked scientifically, and it is found that the accuracy of the logistic regression algorithm for analyzing different reviews based on three classes, i.e., positive, negative, and neutral.

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