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HCI and Smartphone Data at Scale
 

HCI and Smartphone Data at Scale

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  • Start out with a statement that probably won’t be controversial, which is that smartphones are pervasiveAbout 40% of all mobile phones sold today are smartphones, and the number is rapidly growingWhat’s also interestingare trends in how people use these smartphoneshttp://blog.sciencecreative.com/2011/03/16/the-authentic-online-marketer/http://www.generationalinsights.com/millennials-addicted-to-their-smartphones-some-suffer-nomophobia/In fact, Millennials don’t just sleep with their smartphones. 75% use them in bed before going to sleep and 90% check them again first thing in the morning.  Half use them while eating and third use them in the bathroom. A third check them every half hour. Another fifth check them every ten minutes. A quarter of them check them so frequently that they lose count.http://www.androidtapp.com/how-simple-is-your-smartphone-to-use-funny-videos/Pew Research CenterAround 83 percent of those 18- to 29-year-olds sleep with their cell phones within reach. http://persquaremile.com/category/suburbia/
  • Smartphones intimate part of our livesLocation,call logs,SMS,pics, moreCan capture human behavior atunprecedented fidelity and scale
  • http://www.flickr.com/photos/robby_van_moor/478725670/
  • We know these relationships, but computers have an overly simplified model of our relationships, usually just “friend”Can we do better?
  • Image adapted from Real Life Social Network, by Paul Adams
  • Picture of “Robin Sage”
  • to understand the dynamics, structure, and character of a city
  • If you just looked at the geography only, you might break things down as follows…
  • http://www-958.ibm.com/software/data/cognos/manyeyes/visualizations/b2794c5a60c611e18bfd000255111976/comments/b27c2c4060c611e18bfd000255111976
  • DARPAGoogleCMU CyLab
  • Intuitively, if we are co-located in a highly public place, it’s not a very strong signal
  • 2.8m location sightings of 489 volunteers in Pittsburgh
  • 2.8m location sightings of 489 volunteers in Pittsburgh
  • Livehoods useful for recommender systems, e.g. not recommending things across boundaries

HCI and Smartphone Data at Scale HCI and Smartphone Data at Scale Presentation Transcript