The manifest and store data of 870,515 Android mobile applications
Introduced by Narayanan et al. in apk2vec: Semi-supervised multi-view representation learning for profiling Android applications
Involves a crawler to collect data from the Google Play store including the application's metadata and APK files. The manifest files were extracted from the APK files and then processed to extract the features. The data set is composed of 870,515 records/apps, and for each app we produced 48 features. The data set was used to built and test two bootstrap aggregating of multiple XGBoost machine learning classifiers. The dataset were collected between April 2017 and November 2018. We then checked the status of these applications on three different occasions; December 2018, February 2019, and May-June 2019. (2022-06-03)
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