Social Proximity Indicator Application Enhancing Personalization for the User : A User Centric Multimodal Smartphone based Social Proximity Indicator

University essay from KTH/Radio Systems Laboratory (RS Lab)

Abstract:

The smartphone has become an important part of our daily life. It takes advantage of multiple built-in sensors, along with internet connectivity, to provide a variety of services including navigation, weather forecasts, media capturing/sharing, and many more. The smartphone has become a hub for our social interactions, ranging from traditional voice communications through messaging, to online social networking.

There are endless possibilities for a new generation of applications that automatically adapts according to users’ social affinities. The key enabler is to understand the social profile of the user and to realize a Social Proximity Indicator (SPI). This indicator of a user’s social profile includes the user’s location, preferences, common friends, frequent interactions among friends, community membership, and many more attributes. This project addresses the exploitation of the user’s smartphone as a detector of these user’s social contexts in order to infer the social proximity between any 2 (or more) people. The goal of this social proximity indicator is to identify the (current) set of smartphone users that would want to participate in an application specific activity, such as media sharing, group conversation, etc. SPI identifies users based on their social interactions and common preferences.

Based on this SPI, a photo sharing application is proposed and built for the Android smartphone platform. This application uses multiple physical and virtual sensors (hosted by the user’s smartphone) to determine the context of the user. After inferring this context, the application initiates photo sharing among an identified group sharing this context. The application, as well as the underlying code, theoretical concepts, and results are presented in this thesis. The experiments conducted during this thesis project indicate that it is feasible to build smartphone based social proximity based applications in which proximity incorporates much more than simply physical location, thus going beyond existing applications.

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