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Activity Number: 245 - Methods for Analysis of High-Dimensional Data
Type: Contributed
Date/Time: Monday, July 30, 2018 : 2:00 PM to 3:50 PM
Sponsor: SSC
Abstract #326966 Presentation
Title: Capture-Recapture Methods for Data on the Activation of Applications on Mobile Phones
Author(s): Mamadou YAUCK* and Louis-Paul Rivest and Greg Rothman
Companies: Universite Laval and Université Laval and NinthDecimal
Keywords: Heterogeneity; Jolly-Seber model; Poisson regression; Robust design

This work is concerned with the analysis of marketing data on the activation of applications (apps) on mobile devices. Each application has a hashed identification number that is specific to the device on which it has been installed. This number can be registered by a platform at each activation of the application. Activations on the same device are linked together using the identification number. By focusing on activations that took place at a business location one can create a capture-recapture data set about devices, that is users, that "visited" the business: the units are owners of mobile devices and the capture occasions are time intervals such as days. A unit is captured when she activates an application, provided that this activation is recorded by the platform providing the data. Statistical capture-recapture techniques can be applied to the app data to estimate the total number of users that visited the business over a time period, thereby providing an indirect estimate of foot traffic. This article argues that the robust design, a method for dealing with a nested mark-recapture experiment, can be used in this context.

Authors who are presenting talks have a * after their name.

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