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@ -26,7 +26,7 @@ TIME_SEGMENTS: &time_segments
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INCLUDE_PAST_PERIODIC_SEGMENTS: TRUE # Only relevant if TYPE=PERIODIC, see docs
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TAILORED_EVENTS: # Only relevant if TYPE=EVENT
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COMPUTE: True
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SEGMENTING_METHOD: "30_before" # 30_before, 90_before, stress_event
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SEGMENTING_METHOD: "stress_event" # 30_before, 90_before, stress_event
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INTERVAL_OF_INTEREST: 10 # duration of event of interest [minutes]
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IOI_ERROR_TOLERANCE: 5 # interval of interest erorr tolerance (before and after IOI) [minutes]
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@ -104,9 +104,9 @@ PHONE_APPLICATIONS_CRASHES:
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CONTAINER: applications_crashes
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APPLICATION_CATEGORIES:
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CATALOGUE_SOURCE: FILE # FILE (genres are read from CATALOGUE_FILE) or GOOGLE (genres are scrapped from the Play Store)
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CATALOGUE_FILE: "data/external/play_store_application_genre_catalogue.csv"
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UPDATE_CATALOGUE_FILE: False # if CATALOGUE_SOURCE is equal to FILE, whether to update CATALOGUE_FILE, if CATALOGUE_SOURCE is equal to GOOGLE all scraped genres will be saved to CATALOGUE_FILE
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SCRAPE_MISSING_CATEGORIES: False # whether to scrape missing genres, only effective if CATALOGUE_SOURCE is equal to FILE. If CATALOGUE_SOURCE is equal to GOOGLE, all genres are scraped anyway
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CATALOGUE_FILE: "data/external/stachl_application_genre_catalogue.csv"
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UPDATE_CATALOGUE_FILE: False # if CATALOGUE_SOURCE is equal to FILE, whether or not to update CATALOGUE_FILE, if CATALOGUE_SOURCE is equal to GOOGLE all scraped genres will be saved to CATALOGUE_FILE
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SCRAPE_MISSING_CATEGORIES: False # whether or not to scrape missing genres, only effective if CATALOGUE_SOURCE is equal to FILE. If CATALOGUE_SOURCE is equal to GOOGLE, all genres are scraped anyway
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PROVIDERS: # None implemented yet but this sensor can be used in PHONE_DATA_YIELD
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# See https://www.rapids.science/latest/features/phone-applications-foreground/
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@ -114,32 +114,24 @@ PHONE_APPLICATIONS_FOREGROUND:
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CONTAINER: applications
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APPLICATION_CATEGORIES:
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CATALOGUE_SOURCE: FILE # FILE (genres are read from CATALOGUE_FILE) or GOOGLE (genres are scrapped from the Play Store)
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CATALOGUE_FILE: "data/external/play_store_application_genre_catalogue.csv"
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# Refer to data/external/play_store_categories_count.csv for a list of categories (genres) and their frequency.
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UPDATE_CATALOGUE_FILE: False # if CATALOGUE_SOURCE is equal to FILE, whether to update CATALOGUE_FILE, if CATALOGUE_SOURCE is equal to GOOGLE all scraped genres will be saved to CATALOGUE_FILE
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SCRAPE_MISSING_CATEGORIES: False # whether to scrape missing genres, only effective if CATALOGUE_SOURCE is equal to FILE. If CATALOGUE_SOURCE is equal to GOOGLE, all genres are scraped anyway
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CATALOGUE_FILE: "data/external/stachl_application_genre_catalogue.csv"
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PACKAGE_NAMES_HASHED: True
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UPDATE_CATALOGUE_FILE: False # if CATALOGUE_SOURCE is equal to FILE, whether or not to update CATALOGUE_FILE, if CATALOGUE_SOURCE is equal to GOOGLE all scraped genres will be saved to CATALOGUE_FILE
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SCRAPE_MISSING_CATEGORIES: False # whether or not to scrape missing genres, only effective if CATALOGUE_SOURCE is equal to FILE. If CATALOGUE_SOURCE is equal to GOOGLE, all genres are scraped anyway
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PROVIDERS:
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RAPIDS:
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COMPUTE: True
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INCLUDE_EPISODE_FEATURES: True
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SINGLE_CATEGORIES: ["Productivity", "Tools", "Communication", "Education", "Social"]
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SINGLE_CATEGORIES: ["all", "email"]
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MULTIPLE_CATEGORIES:
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games: ["Puzzle", "Card", "Casual", "Board", "Strategy", "Trivia", "Word", "Adventure", "Role Playing", "Simulation", "Board, Brain Games", "Racing"]
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social: ["Communication", "Social", "Dating"]
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productivity: ["Tools", "Productivity", "Finance", "Education", "News & Magazines", "Business", "Books & Reference"]
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health: ["Health & Fitness", "Lifestyle", "Food & Drink", "Sports", "Medical", "Parenting"]
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entertainment: ["Shopping", "Music & Audio", "Entertainment", "Travel & Local", "Photography", "Video Players & Editors", "Personalization", "House & Home", "Art & Design", "Auto & Vehicles", "Entertainment,Music & Video",
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"Puzzle", "Card", "Casual", "Board", "Strategy", "Trivia", "Word", "Adventure", "Role Playing", "Simulation", "Board, Brain Games", "Racing" # Add all games.
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]
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maps_weather: ["Maps & Navigation", "Weather"]
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social: ["socialnetworks", "socialmediatools"]
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entertainment: ["entertainment", "gamingknowledge", "gamingcasual", "gamingadventure", "gamingstrategy", "gamingtoolscommunity", "gamingroleplaying", "gamingaction", "gaminglogic", "gamingsports", "gamingsimulation"]
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CUSTOM_CATEGORIES:
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SINGLE_APPS: []
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EXCLUDED_CATEGORIES: ["System", "STRAW"]
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# Note: A special option here is "is_system_app".
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# This excludes applications that have is_system_app = TRUE, which is a separate column in the table.
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# However, all of these applications have been assigned System category.
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# I will therefore filter by that category, which is a superset and is more complete. JL
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EXCLUDED_APPS: []
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social_media: ["com.google.android.youtube", "com.snapchat.android", "com.instagram.android", "com.zhiliaoapp.musically", "com.facebook.katana"]
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dating: ["com.tinder", "com.relance.happycouple", "com.kiwi.joyride"]
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SINGLE_APPS: ["top1global", "com.facebook.moments", "com.google.android.youtube", "com.twitter.android"] # There's no entropy for single apps
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EXCLUDED_CATEGORIES: []
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EXCLUDED_APPS: ["com.fitbit.FitbitMobile", "com.aware.plugin.upmc.cancer"] # TODO list system apps?
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FEATURES:
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APP_EVENTS: ["countevent", "timeoffirstuse", "timeoflastuse", "frequencyentropy"]
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APP_EPISODES: ["countepisode", "minduration", "maxduration", "meanduration", "sumduration"]
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@ -753,6 +745,6 @@ PARAMS_FOR_ANALYSIS:
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TARGET:
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COMPUTE: True
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LABEL: appraisal_stressfulness_event_mean
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ALL_LABELS: [PANAS_positive_affect_mean, PANAS_negative_affect_mean, JCQ_job_demand_mean, JCQ_job_control_mean, JCQ_supervisor_support_mean, JCQ_coworker_support_mean, appraisal_stressfulness_period_mean]
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ALL_LABELS: [appraisal_stressfulness_event_mean, appraisal_threat_mean, appraisal_challenge_mean]
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# PANAS_positive_affect_mean, PANAS_negative_affect_mean, JCQ_job_demand_mean, JCQ_job_control_mean, JCQ_supervisor_support_mean,
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# JCQ_coworker_support_mean, appraisal_stressfulness_period_mean, appraisal_stressfulness_event_mean, appraisal_threat_mean, appraisal_challenge_mean
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