Context Data Categories and Privacy Model for Mobile Data Collection Apps

TL;DR

This paper introduces TYDR, an Android app that collects diverse smartphone data to predict user personality traits, along with a general context data model and a privacy framework to support privacy-aware mobile data collection.

Contribution

It presents a comprehensive context data model and a privacy model tailored for mobile data collection, and implements these in the TYDR app to facilitate personality prediction research.

Findings

TYDR collects extensive smartphone data including notifications, photos, and music.

The proposed privacy measures are implemented successfully in TYDR.

The approach shows promise for enhancing context-aware mobile applications.

Abstract

Context-aware applications stemming from diverse fields like mobile health, recommender systems, and mobile commerce potentially benefit from knowing aspects of the user's personality. As filling out personality questionnaires is tedious, we propose the prediction of the user's personality from smartphone sensor and usage data. In order to collect data for researching the relationship between smartphone data and personality, we developed the Android app TYDR (Track Your Daily Routine) which tracks smartphone data and utilizes psychometric personality questionnaires. With TYDR, we track a larger variety of smartphone data than similar existing apps, including metadata on notifications, photos taken, and music played back by the user. For the development of TYDR, we introduce a general context data model consisting of four categories that focus on the user's different types of interactions with the smartphone: physical conditions and activity, device status and usage, core functions usage, and app usage. On top of this, we develop the privacy model PM-MoDaC specifically for apps related to the collection of mobile data, consisting of nine proposed privacy measures. We present the implementation of all of those measures in TYDR. Although the utilization of the user's personality based on the usage of his or her smartphone is a challenging endeavor, it seems to be a promising approach for various types of context-aware mobile applications.