Phone Applications Foreground¶
Sensor parameters description for [PHONE_APPLICATIONS_FOREGROUND] (these parameters are used by the only provider available at the moment, RAPIDS):
| Key | Description |
|---|---|
[TABLE] |
Database table where the applications foreground data is stored |
[APPLICATION_CATEGORIES][CATALOGUE_SOURCE] |
FILE or GOOGLE. If FILE, app categories (genres) are read from [CATALOGUE_FILE]. If [GOOGLE], app categories (genres) are scrapped from the Play Store |
[APPLICATION_CATEGORIES][CATALOGUE_FILE] |
CSV file with a package_name and genre column. By default we provide the catalogue created by Stachl et al in data/external/stachl_application_genre_catalogue.csv |
[APPLICATION_CATEGORIES][UPDATE_CATALOGUE_FILE] |
if [CATALOGUE_SOURCE] is equal to FILE, this flag signals whether or not to update [CATALOGUE_FILE], if [CATALOGUE_SOURCE] is equal to GOOGLE all scraped genres will be saved to [CATALOGUE_FILE] |
[APPLICATION_CATEGORIES][SCRAPE_MISSING_CATEGORIES] |
This flag signals whether or not to scrape categories (genres) missing from the [CATALOGUE_FILE]. If [CATALOGUE_SOURCE] is equal to GOOGLE, all genres are scraped anyway (this flag is ignored) |
RAPIDS provider¶
The app category (genre) catalogue used in these features was originally created by Stachl et al.
Available time segments and platforms
- Available for all time segments
- Available for Android only
File Sequence
- data/raw/{pid}/phone_applications_foreground_raw.csv
- data/raw/{pid}/phone_applications_foreground_with_datetime.csv
- data/raw/{pid}/phone_applications_foreground_with_datetime_with_categories.csv
- data/interim/{pid}/phone_applications_foreground_features/phone_applications_foreground_{language}_{provider_key}.csv
- data/processed/features/{pid}/phone_applications_foreground.csv
Parameters description for [PHONE_APPLICATIONS_FOREGROUND][PROVIDERS][RAPIDS]:
| Key | Description |
|---|---|
[COMPUTE] |
Set to True to extract PHONE_APPLICATIONS_FOREGROUND features from the RAPIDS provider |
[FEATURES] |
Features to be computed, see table below |
[SINGLE_CATEGORIES] |
An array of app categories to be included in the feature extraction computation. The special keyword all represents a category with all the apps from each participant. By default we use the category catalogue pointed by [APPLICATION_CATEGORIES][CATALOGUE_FILE] (see the Sensor parameters description table above) |
[MULTIPLE_CATEGORIES] |
An array of collections representing meta-categories (a group of categories). They key of each element is the name of the meta-category and the value is an array of member app categories. By default we use the category catalogue pointed by [APPLICATION_CATEGORIES][CATALOGUE_FILE] (see the Sensor parameters description table above) |
[SINGLE_APPS] |
An array of apps to be included in the feature extraction computation. Use their package name (e.g. com.google.android.youtube) or the reserved keyword top1global (the most used app by a participant over the whole monitoring study) |
[EXCLUDED_CATEGORIES] |
An array of app categories to be excluded from the feature extraction computation. By default we use the category catalogue pointed by [APPLICATION_CATEGORIES][CATALOGUE_FILE] (see the Sensor parameters description table above) |
[EXCLUDED_APPS] |
An array of apps to be excluded from the feature extraction computation. Use their package name, for example: com.google.android.youtube |
Features description for [PHONE_APPLICATIONS_FOREGROUND][PROVIDERS][RAPIDS]:
| Feature | Units | Description |
|---|---|---|
| count | apps | Number of times a single app or apps within a category were used (i.e. they were brought to the foreground either by tapping their icon or switching to it from another app) |
| timeoffirstuse | minutes | The time in minutes between 12:00am (midnight) and the first use of a single app or apps within a category during a time_segment |
| timeoflastuse | minutes | The time in minutes between 12:00am (midnight) and the last use of a single app or apps within a category during a time_segment |
| frequencyentropy | nats | The entropy of the used apps within a category during a time_segment (each app is seen as a unique event, the more apps were used, the higher the entropy). This is especially relevant when computed over all apps. Entropy cannot be obtained for a single app |
Assumptions/Observations
Features can be computed by app, by apps grouped under a single category (genre) and by multiple categories grouped together (meta-categories). For example, we can get features for Facebook (single app), for Social Network apps (a category including Facebook and other social media apps) or for Social (a meta-category formed by Social Network and Social Media Tools categories).
Apps installed by default like YouTube are considered systems apps on some phones. We do an exact match to exclude apps where “genre” == EXCLUDED_CATEGORIES or “package_name” == EXCLUDED_APPS.
We provide three ways of classifying and app within a category (genre): a) by automatically scraping its official category from the Google Play Store, b) by using the catalogue created by Stachl et al. which we provide in RAPIDS (data/external/stachl_application_genre_catalogue.csv), or c) by manually creating a personalized catalogue. You can choose a, b or c by modifying [APPLICATION_GENRES] keys and values (see the Sensor parameters description table above).