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Strategies and limitations in app usage and human mobility Marco De Nadai, Antonio Lima, Angelo Cardoso, Bruno Lepri and Nuria Oliver

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2 Photo: Liz Hafalia, The Chronicle + NBC News

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3 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%

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4 ALWAYS USED But I always use the same apps!

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5 ALWAYS USED MEH... SOMETIMES But I always use the same apps!

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

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7 Monotony vs Growth of app usage

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8 •Screen time of 90K people •Over 8 months •69K different apps •12M of people’s hours spent on apps Data

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9 Data (pseudo-anonymized)

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10 Data (pseudo-anonymized)

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11 Data (pseudo-anonymized)

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12 Data (pseudo-anonymized) •Screen time •No network-based approaches •Unique dataset of app usage

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13 • " ~ ( + ' ))*), - • = 1.19 ± 0.01 Characterizing App usage

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14 • " ~ ( + ' ))*), - • = 1.19 ± 0.01 Characterizing App usage • " ~ ())* • = 1.27 ± 0.01

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15 • " ~ ( + ' ))*), - • = 1.19 ± 0.01 Characterizing App usage • " ~ ())* • = 1.27 ± 0.01 • ~ 9 • γ = 0.41

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16 • " ~ ( + ' ))*), - • = 1.19 ± 0.01 Characterizing App usage • " ~ ())* • = 1.27 ± 0.01 • ~ 9 • γ = 0.41 • PEOPLE TIME IS FOCUSED ON FEW APPS • PEOPLE KEEP EXPLORING NEW APPS

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17 The familiar apps over time: the App space THE APP SPACE (t)

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18 • 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

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App space over time (adopted and dropped apps) < < = (<) = 4 THE APP SPACE (t)

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App space over time (adopted and dropped apps) B < < = (<) = 4 B = (B) = 5 THE APP SPACE (t)

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App space over time (adopted and dropped apps) D B < < = (<) = 4 B = (B) = 5 D = (D) = 4 THE APP SPACE (t)

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App space over time (adopted and dropped apps) <)B = <)B = B)D = B)D = D B < < = (<) = 4 B = (B) = 5 D = (D) = 4 THE APP SPACE (t)

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23 • Gain: M = M − M () • 97.5% of people exhibit a conserved capacity ( OP QRP ≤ 1) Adoped and dropped apps

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

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25 •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? < B D T USER A D T < B < B D T USER A < B D T < B D T USER B < B D T

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

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27 What about age?

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28 What about age?

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29 What about age? 16 What about age?

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30 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?

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31 Then?

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32 Strategies and limitations in app usage and human mobility https://arxiv.org/abs/1904.09350

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33 Apps, Mobility, Social interactions are conserved DUNBAR’S NUMBER OF APPS?

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ANGELO CARDOSO BRUNO LEPRI ANTONIO LIMA Thank you! @denadai2 NURIA OLIVER

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35 • Alessandretti, Laura, et al. "Evidence for a conserved quantity in human mobility." Nature human behaviour 2.7 (2018): 485. • Alessandretti, Laura, Sune Lehmann, and Andrea Baronchelli. "Understanding the interplay between social and spatial behaviour." EPJ Data Science 7.1 (2018): 36. • Pappalardo, Luca, et al. "Returners and explorers dichotomy in human mobility." Nature communications 6 (2015): 8166. • Miritello, Giovanna, et al. "Limited communication capacity unveils strategies for human interaction." Scientific reports 3 (2013): 1950. References

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36 Apps that stay the most ~10% of apps are always kept ~17.5% are continuosly changed

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37 Strategy vs age