Mobile Applications Rating Performance: A Survey

International Journal of Interactive Mobile Technologies

article

Sabreen Abulhaija¹  Shayma Hattab²  Ahmad Abdeen²  Wael Etaiwi² 

[1] Princess Sumaya University for Technology;King Talal School of Business Technology, Princess Sumaya University for Technology

关键词: Machine Learning;    Mobile Applications;    Rating Performance;    Sentiment Analysis;    Predictive Modeling;   

DOI  :  10.3991/ijim.v16i19.32051

学科分类：社会科学、人文和艺术（综合）

来源: International Association of Online Engineering

【 摘 要 】

The use of mobile phones is increasing all the time. These phones have become increasingly vital and beneficial in all parts of our lives, including social and business sides. Mobile applications are expanding with new upgrades and editions every day due to this expansion. This increase makes it more difficult for consumers, particularly those who are not technologically minded, to determine which applications to install and use. It is much more difficult for developers to ensure that their apps will be used and lucrative. Several research papers have been published in the recent five years to investigate mobile applications' rating to aid users and developers in making the best decision possible by employing various classifications and methodologies. This study provides a literature review research analyzed mobile app evaluations from 2018 to 2022 using various datasets.  In addition, a new taxonomy is proposed to classify the research papers that looked at the rating of mobile apps into three categories: predictive modeling, sentiment analysis, and priority ranking of the most significant features.

【 授权许可】

CC BY