Mobile applications quality evaluation according to ISO 9126 quality model using Naïve Bayes

In this study a tool to evaluate the quality of mobile applications from the user provided reviews in Google Play app store is developed. ISO 9126 quality in use part is used as the quality model. We used a supervised Machine learning technique to undertake this project. Specifically, Weka Naïve Bay...

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Main Author:	Ali, Jabir Abdullahi
Format:	Thesis
Language:	English
Published:	2018
Subjects:	Mobile apps - Evaluation
Online Access:	http://psasir.upm.edu.my/id/eprint/69053/1/FSKTM%202018%2060%20IR.pdf
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id	my-upm-ir.69053
record_format	uketd_dc
spelling	my-upm-ir.690532019-06-17T01:28:41Z Mobile applications quality evaluation according to ISO 9126 quality model using Naïve Bayes 2018-05 Ali, Jabir Abdullahi In this study a tool to evaluate the quality of mobile applications from the user provided reviews in Google Play app store is developed. ISO 9126 quality in use part is used as the quality model. We used a supervised Machine learning technique to undertake this project. Specifically, Weka Naïve Bayes classifier is employed. We downloaded 2000 reviews from Google play, used 70% for training the classifying model and 30% for testing the model. The outcome of the manual labelling of the reviews is that 96% of the reviews are categorized as either satisfaction or effectiveness. This suggests that users tend to talk more about how they like or dislike a mobile app or complain about the ineffectiveness of it. Due to this skewed nature of the data, the classifying model testing part of the study yielded the expected outcome. The model precision is high for both Satisfaction and effectiveness quality characteristics of the ISO 9126 quality in use part, since both of them got large training data sets. However, due to the minimal training reviews received by the safety and productivity categories their precision lags. Therefore, the study suggests that users are more concerned about the effectiveness of an app and how satisfied the use of the app and its features makes them. Mobile apps - Evaluation 2018-05 Thesis http://psasir.upm.edu.my/id/eprint/69053/ http://psasir.upm.edu.my/id/eprint/69053/1/FSKTM%202018%2060%20IR.pdf text en public masters Universiti Putra Malaysia Mobile apps - Evaluation
institution	Universiti Putra Malaysia
collection	PSAS Institutional Repository
language	English
topic	Mobile apps - Evaluation
spellingShingle	Mobile apps - Evaluation Ali, Jabir Abdullahi Mobile applications quality evaluation according to ISO 9126 quality model using Naïve Bayes
description	In this study a tool to evaluate the quality of mobile applications from the user provided reviews in Google Play app store is developed. ISO 9126 quality in use part is used as the quality model. We used a supervised Machine learning technique to undertake this project. Specifically, Weka Naïve Bayes classifier is employed. We downloaded 2000 reviews from Google play, used 70% for training the classifying model and 30% for testing the model. The outcome of the manual labelling of the reviews is that 96% of the reviews are categorized as either satisfaction or effectiveness. This suggests that users tend to talk more about how they like or dislike a mobile app or complain about the ineffectiveness of it. Due to this skewed nature of the data, the classifying model testing part of the study yielded the expected outcome. The model precision is high for both Satisfaction and effectiveness quality characteristics of the ISO 9126 quality in use part, since both of them got large training data sets. However, due to the minimal training reviews received by the safety and productivity categories their precision lags. Therefore, the study suggests that users are more concerned about the effectiveness of an app and how satisfied the use of the app and its features makes them.
format	Thesis
qualification_level	Master's degree
author	Ali, Jabir Abdullahi
author_facet	Ali, Jabir Abdullahi
author_sort	Ali, Jabir Abdullahi
title	Mobile applications quality evaluation according to ISO 9126 quality model using Naïve Bayes
title_short	Mobile applications quality evaluation according to ISO 9126 quality model using Naïve Bayes
title_full	Mobile applications quality evaluation according to ISO 9126 quality model using Naïve Bayes
title_fullStr	Mobile applications quality evaluation according to ISO 9126 quality model using Naïve Bayes
title_full_unstemmed	Mobile applications quality evaluation according to ISO 9126 quality model using Naïve Bayes
title_sort	mobile applications quality evaluation according to iso 9126 quality model using naïve bayes
granting_institution	Universiti Putra Malaysia
publishDate	2018
url	http://psasir.upm.edu.my/id/eprint/69053/1/FSKTM%202018%2060%20IR.pdf
_version_	1747812661397028864

Mobile applications quality evaluation according to ISO 9126 quality model using Naïve Bayes

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