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Conserved capacity of app usage - Data Science ...

Marco De Nadai
November 19, 2020

Conserved capacity of app usage - Data Science Lecture

Marco De Nadai

November 19, 2020
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  1. 2

  2. 7 THERE ARE 2.1M APPS IN THE GOOGLE PLAY STORE

    App usage statistics by Statista.com & hubspot.net
  3. 8 PEOPLE SPEND AN INCREASINGLY AMOUNT OF TIME ON THE

    PHONE […] REACHING 3 HOURS PER DAY THERE ARE 2.1M APPS IN THE GOOGLE PLAY STORE App usage statistics by Statista.com & hubspot.net
  4. 9 PEOPLE SPEND AN INCREASINGLY AMOUNT OF TIME ON THE

    PHONE […] REACHING 3 HOURS PER DAY THERE ARE 2.1M APPS IN THE GOOGLE PLAY STORE App usage statistics by Statista.com & hubspot.net USER ENGAGMENT INCREASED BY 23%
  5. 17 ALWAYS USED MEH... SOMETIMES WAS THIS APP EVEN HERE?

    • APP USAGE CHANGES • APPS CHANGE But I always use the same apps!
  6. 18 ALWAYS USED MEH... SOMETIMES WAS THIS APP EVEN HERE?

    • APP USAGE CHANGES • APPS CHANGE But I always use the same apps!
  7. 20 •Screen time of 90K people •Over 8 months •69K

    different apps •12M of people’s hours spent on apps Data
  8. 23 • ! ~ ( + " )#$#! " •

    = 1.19 ± 0.01 Characterizing App usage
  9. 24 • ! ~ ( + " )#$#! " •

    = 1.19 ± 0.01 Characterizing App usage • ! ~ ()#$ • = 1.27 ± 0.01
  10. 25 • ! ~ ( + " )#$#! " •

    = 1.19 ± 0.01 Characterizing App usage • ! ~ ()#$ • = 1.27 ± 0.01 • ~ % • γ = 0.41
  11. 26 • ! ~ ( + " )#$#! " •

    = 1.19 ± 0.01 Characterizing App usage • ! ~ ()#$ • = 1.27 ± 0.01 • ~ % • γ = 0.41 • PEOPLE TIME IS FOCUSED ON FEW APPS • PEOPLE KEEP EXPLORING NEW APPS
  12. 28 • Apps used at least twice and for at

    least 10 min per week • 20 weeks long sliding windows (1 week) • How does the App space evolve over time? The familiar apps over time: the App space THE APP SPACE (t) THE APP SPACE (t-1) THE APP SPACE (t+1) 1 WEEK 1 WEEK
  13. App space over time (adopted and dropped apps) " !

    ! = (!) = 4 " = (") = 5 THE APP SPACE (t)
  14. App space over time (adopted and dropped apps) # "

    ! ! = (!) = 4 " = (") = 5 # = (#) = 4 THE APP SPACE (t)
  15. App space over time (adopted and dropped apps) !$" =

    !$" = "$# = "$# = # " ! ! = (!) = 4 " = (") = 5 # = (#) = 4 THE APP SPACE (t)
  16. 35 • Gain: 3 = 3 − 3 () •

    97.5% of people exhibit a conserved capacity ( 4# 5$# ≤ 1) Adoped and dropped apps
  17. What is the conserved capacity? On average: •Everytime a new

    app is adopted, an older app is discarded THE APP SPACE (t)
  18. What is the conserved capacity? On average: •Everytime a new

    app is adopted, an older app is discarded THE APP SPACE (t)
  19. What is the conserved capacity? On average: •Everytime a new

    app is adopted, an older app is discarded THE APP SPACE (t)
  20. What is the conserved capacity? On average: •Everytime a new

    app is adopted, an older app is discarded THE APP SPACE (t)
  21. 40 •Local shuffle: app usage order of a user •If

    the random permutated user has the same capacity => Time •Two-sample Kolmogorov–Smirnov test •Set p-value threshold (0.05 or 0.001?) - Different (p-value < threshold) - Don’t know (p-value > threshold) Is capacity a time-constraints consequence? ! " # $ USER A # $ ! " https://en.wikipedia.org/wiki/Kolmogorov%E2%80%93Smirnov_test
  22. 41 •Local shuffle: app usage order of a user No

    time consequence (KS: 0.55 p-value < 0.001). •Global: app usage among users (KS: 0.98 p-value < 0.001). It’s an individual characteristics. Is capacity a time-constraints consequence? ! " # $ USER A # $ ! " ! " # $ USER A ! " # $ ! " # $ USER B ! " # $
  23. 42 The app strategy • EXPLORERS (% ≫ ) •

    KEEPERS (% ≪ ) • Explorers adopt 1 new app every 28 weeks • Keepers always keep using the same apps % = % / %
  24. 43 The app strategy • EXPLORERS (% ≫ ) •

    KEEPERS (% ≪ ) • Explorers adopt 1 new app every 28 weeks • Keepers always keep using the same apps % = % / %
  25. 44 The app strategy • EXPLORERS (% ≫ ) •

    KEEPERS (% ≪ ) • Explorers adopt 1 new app every 28 weeks • Keepers always keep using the same apps % = % / %
  26. 48 People are focused on few apps, but keep exploring.

    Individuals exhibit a conserved app capacity •Capacity is an individual behaviour •Capacity varies with age •We can define app explorers and keepers •AND MORE! So?
  27. 53 Apps that stay the most ~10% of apps are

    always kept ~17.5% are continuosly changed
  28. 57

  29. 58

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  32. 61

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  35. 64

  36. 66 Individuals exhibit a conserved app capacity •To explore dataaa

    •Understand complex queries •A bit of spark What did I learn?
  37. 67 Individuals exhibit a conserved app capacity •To explore dataaa

    •Understand complex queries •A bit of spark What did I learn?
  38. 68 Individuals exhibit a conserved app capacity •To explore dataaa

    •Understand complex queries •A bit of spark What did I learn?