Analysis and Classification of Mobile Apps Using Topic Modeling: A Case Study on Google Play Arabic Apps

Mobile app stores provide an extremely rich source of information on app descriptions, characteristics, and usage, and analyzing these data provides insights and a deeper understanding of the nature of apps. However, manual analysis of this vast amount of information on mobile apps is not a simple a...

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Main Authors: Ahlam Fuad, Maha Al-Yahya
Format: Article
Language:English
Published: Wiley 2021-01-01
Series:Complexity
Online Access:http://dx.doi.org/10.1155/2021/6677413
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author Ahlam Fuad
Maha Al-Yahya
author_facet Ahlam Fuad
Maha Al-Yahya
author_sort Ahlam Fuad
collection DOAJ
description Mobile app stores provide an extremely rich source of information on app descriptions, characteristics, and usage, and analyzing these data provides insights and a deeper understanding of the nature of apps. However, manual analysis of this vast amount of information on mobile apps is not a simple and straightforward task; it is costly in terms of human effort and time. Computational methods such as topic modeling can provide an efficient and satisfactory approach to mobile app information analysis. Topic modeling is a type of statistical modeling technique for discovering abstract topics that occur in a set of documents. This study explores the relationship between features of Arabic apps and investigates how well the current predefined Google Play app categories represent the type and genre of Arabic mobile apps. Based on the textual app description analysis, we aim to design and develop a sustainable classification system using the Latent Dirichlet Allocation (LDA) method of topic modeling in order to cover the Arabic apps classification in Google Play app store. Our study supports the hypothesis that the textual app descriptions are effective in suggesting new categories for Arabic mobile apps in Google Play app store. Also, the results indicated that the current classification on Google Play app store is not suitable for our case study “Arabic apps,” as well as it is not sustainable, as it can not cover the new app types including Arabic apps. This study offers an important contribution to Arabic app analysis and design, to improve app search and exploration in several domains such as business, marketing, and technical development. Furthermore, it provides insights for the future of Arabic app research and provides guidance for the development of an Arabic app dashboard that will support users on how to select an app based on their specific needs.
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spelling doaj-art-11ef7ed3cb514dc9b79a54fd8b8482b12025-02-03T06:43:56ZengWileyComplexity1076-27871099-05262021-01-01202110.1155/2021/66774136677413Analysis and Classification of Mobile Apps Using Topic Modeling: A Case Study on Google Play Arabic AppsAhlam Fuad0Maha Al-Yahya1Department of Information Technology, College of Computer and Information Sciences, King Saud University, P.O. Box 145111, Zip 4545, Riyadh, Saudi ArabiaDepartment of Information Technology, College of Computer and Information Sciences, King Saud University, P.O. Box 145111, Zip 4545, Riyadh, Saudi ArabiaMobile app stores provide an extremely rich source of information on app descriptions, characteristics, and usage, and analyzing these data provides insights and a deeper understanding of the nature of apps. However, manual analysis of this vast amount of information on mobile apps is not a simple and straightforward task; it is costly in terms of human effort and time. Computational methods such as topic modeling can provide an efficient and satisfactory approach to mobile app information analysis. Topic modeling is a type of statistical modeling technique for discovering abstract topics that occur in a set of documents. This study explores the relationship between features of Arabic apps and investigates how well the current predefined Google Play app categories represent the type and genre of Arabic mobile apps. Based on the textual app description analysis, we aim to design and develop a sustainable classification system using the Latent Dirichlet Allocation (LDA) method of topic modeling in order to cover the Arabic apps classification in Google Play app store. Our study supports the hypothesis that the textual app descriptions are effective in suggesting new categories for Arabic mobile apps in Google Play app store. Also, the results indicated that the current classification on Google Play app store is not suitable for our case study “Arabic apps,” as well as it is not sustainable, as it can not cover the new app types including Arabic apps. This study offers an important contribution to Arabic app analysis and design, to improve app search and exploration in several domains such as business, marketing, and technical development. Furthermore, it provides insights for the future of Arabic app research and provides guidance for the development of an Arabic app dashboard that will support users on how to select an app based on their specific needs.http://dx.doi.org/10.1155/2021/6677413
spellingShingle Ahlam Fuad
Maha Al-Yahya
Analysis and Classification of Mobile Apps Using Topic Modeling: A Case Study on Google Play Arabic Apps
Complexity
title Analysis and Classification of Mobile Apps Using Topic Modeling: A Case Study on Google Play Arabic Apps
title_full Analysis and Classification of Mobile Apps Using Topic Modeling: A Case Study on Google Play Arabic Apps
title_fullStr Analysis and Classification of Mobile Apps Using Topic Modeling: A Case Study on Google Play Arabic Apps
title_full_unstemmed Analysis and Classification of Mobile Apps Using Topic Modeling: A Case Study on Google Play Arabic Apps
title_short Analysis and Classification of Mobile Apps Using Topic Modeling: A Case Study on Google Play Arabic Apps
title_sort analysis and classification of mobile apps using topic modeling a case study on google play arabic apps
url http://dx.doi.org/10.1155/2021/6677413
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