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Empirical Models of Privacy in Location Sharing

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Recently, I presented our paper "Empirical models of privacy in location sharing" (PDF) in Ucibomp - a great conference about mobile computing. The idea behind the paper is to study what type of …

Recently, I presented our paper "Empirical models of privacy in location sharing" (PDF) in Ucibomp - a great conference about mobile computing. The idea behind the paper is to study what type of privacy preferences people assign to distinct places in location sharing scenarios (e.g., when using applications such as Foursquare, Facebook Places and Google Latitude). In order to study this question, we asked 28 people to use our location sharing application, Locaccino, with their actual friends for a month. We found out that people are more likely to share places with high entropy: places which are visited frequently by a diverse population. Entropy is a super-easy method for predicting which places will be shared. Also, we have seen that users who visit lots of low entropy places are more likely to have more privacy concerns and more restrictive privacy preferences.

You can find more information about the paper here: http://bit.ly/aRLqje

Published in: Technology, Economy & Finance
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  • The one measure that was significant was location entropy
  • The one measure that was significant was location entropy
  • The one measure that was significant was location entropy
  • The one measure that was significant was location entropy
  • We showed unique locations - 500 meters away from other places
    And only locations in which they were 5 minutes or more














  • Number of observations has a bias in in homes. If users visits their home a lot, then they will have high entropy.

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