An automated mobile app labeling framework based on primary motivations for smartphone use
International Journal of Web Information Systems
ISSN: 1744-0084
Article publication date: 3 November 2021
Issue publication date: 2 February 2022
Abstract
Purpose
This paper aims to propose an automated mobile app labeling framework based on a novel app classification scheme that is aligned with users’ primary motivations for using smartphones. The study addresses the gaps in incorporating the needs of users and other context information in app classification as well as recommendation systems.
Design/methodology/approach
Based on a corpus of mobile app descriptions collected from Google Play store, this study applies extensive text analytics and topic modeling procedures to profile mobile apps within the categories of the classification scheme. Sufficient number of representative and labeled app descriptions are then used to train a classifier using machine learning algorithms, such as rule-based, decision tree and artificial neural network.
Findings
Experimental results of the classifiers show high accuracy in automatically labeling new apps based on their descriptions. The accuracy of the classification results suggests a feasible direction in facilitating app searching and retrieval in different Web-based usage environments.
Research limitations/implications
As a common challenge in textual data projects, the problem of data size and data quality issues exists throughout the multiple phases of experiments. Future research will extend the data collection scope in many aspects to address the issues that constrained the current experiments.
Practical implications
These empirical experiments demonstrate the feasibility of textual data analysis in profiling apps and user context information. This study also benefits app developers by improving app descriptions through a better understanding of user needs and context information. Finally, the classification framework can also guide practitioners in customizing products and services beyond mobile apps where context information and user needs play an important role.
Social implications
Given the widespread usage and applications of smartphones today, the proposed app classification framework will have broader implications to different Web-based application environments.
Originality/value
While there have been other classification approaches in the literature, to the best of the authors’ knowledge, this framework is the first study on building an automated app labeling framework based on primary motivations of smartphone usage.
Keywords
Citation
Ayanso, A., Han, M. and Zihayat, M. (2022), "An automated mobile app labeling framework based on primary motivations for smartphone use", International Journal of Web Information Systems, Vol. 18 No. 1, pp. 23-40. https://doi.org/10.1108/IJWIS-08-2021-0085
Publisher
:Emerald Publishing Limited
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