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Predicting android app success before google play store launch using machine learning

The Google Play Store serves as a pivotal platform for Android app developers, drawing millions of users globally. With an overwhelming influx of new apps introduced daily, developers are faced with the critical challenge of sustaining market share amidst fierce competition. Predicting an app’s succ...

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Main Authors: Aleem, Muhammad, Noorhuzaimi, Mohd Noor
Format: Article
Language:English
English
Published: Elsevier 2024
Subjects:
QA75 Electronic computers. Computer science
Online Access:http://umpir.ump.edu.my/id/eprint/42620/1/Predicting%20android%20app%20success%20before%20google%20play%20store%20launch%20using%20machine%20learning_ABST.pdf
http://umpir.ump.edu.my/id/eprint/42620/2/Predicting%20android%20app%20success%20before%20google%20play%20store%20launch%20using%20machine%20learning.pdf
http://umpir.ump.edu.my/id/eprint/42620/
https://bpasjournals.com/library-science/index.php/journal/article/view/641
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spelling my.ump.umpir.426202024-09-20T03:22:54Z http://umpir.ump.edu.my/id/eprint/42620/ Predicting android app success before google play store launch using machine learning Aleem, Muhammad Noorhuzaimi, Mohd Noor QA75 Electronic computers. Computer science The Google Play Store serves as a pivotal platform for Android app developers, drawing millions of users globally. With an overwhelming influx of new apps introduced daily, developers are faced with the critical challenge of sustaining market share amidst fierce competition. Predicting an app’s success before its official launch can provide a strategic advantage, potentially transforming how developers approach app releases. In this study, we aim to forecast the success of new Android apps by predicting key indicators such as user ratings and installation numbers prior to their debut on the Google Play Store. Leveraging machine learning techniques, we analyze historical app data and various app features to build predictive models that offer valuable insights into app performance, empowering developers to make data-driven decisions before launch. Elsevier 2024-07-31 Article PeerReviewed pdf en http://umpir.ump.edu.my/id/eprint/42620/1/Predicting%20android%20app%20success%20before%20google%20play%20store%20launch%20using%20machine%20learning_ABST.pdf pdf en http://umpir.ump.edu.my/id/eprint/42620/2/Predicting%20android%20app%20success%20before%20google%20play%20store%20launch%20using%20machine%20learning.pdf Aleem, Muhammad and Noorhuzaimi, Mohd Noor (2024) Predicting android app success before google play store launch using machine learning. Library Progress International, 44 (3). pp. 1907-1918. ISSN 2320-317X. (Published) https://bpasjournals.com/library-science/index.php/journal/article/view/641
institution Universiti Malaysia Pahang Al-Sultan Abdullah
building UMPSA Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Malaysia Pahang Al-Sultan Abdullah
content_source UMPSA Institutional Repository
url_provider http://umpir.ump.edu.my/
language English
English
topic QA75 Electronic computers. Computer science
spellingShingle QA75 Electronic computers. Computer science
Aleem, Muhammad
Noorhuzaimi, Mohd Noor
Predicting android app success before google play store launch using machine learning
description The Google Play Store serves as a pivotal platform for Android app developers, drawing millions of users globally. With an overwhelming influx of new apps introduced daily, developers are faced with the critical challenge of sustaining market share amidst fierce competition. Predicting an app’s success before its official launch can provide a strategic advantage, potentially transforming how developers approach app releases. In this study, we aim to forecast the success of new Android apps by predicting key indicators such as user ratings and installation numbers prior to their debut on the Google Play Store. Leveraging machine learning techniques, we analyze historical app data and various app features to build predictive models that offer valuable insights into app performance, empowering developers to make data-driven decisions before launch.
format Article
author Aleem, Muhammad
Noorhuzaimi, Mohd Noor
author_facet Aleem, Muhammad
Noorhuzaimi, Mohd Noor
author_sort Aleem, Muhammad
title Predicting android app success before google play store launch using machine learning
title_short Predicting android app success before google play store launch using machine learning
title_full Predicting android app success before google play store launch using machine learning
title_fullStr Predicting android app success before google play store launch using machine learning
title_full_unstemmed Predicting android app success before google play store launch using machine learning
title_sort predicting android app success before google play store launch using machine learning
publisher Elsevier
publishDate 2024
url http://umpir.ump.edu.my/id/eprint/42620/1/Predicting%20android%20app%20success%20before%20google%20play%20store%20launch%20using%20machine%20learning_ABST.pdf
http://umpir.ump.edu.my/id/eprint/42620/2/Predicting%20android%20app%20success%20before%20google%20play%20store%20launch%20using%20machine%20learning.pdf
http://umpir.ump.edu.my/id/eprint/42620/
https://bpasjournals.com/library-science/index.php/journal/article/view/641
_version_ 1822924665891323904
score 13.235362

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