Social Data Mining through Distributed Mobile Sensing
This work addresses the challenge of collecting social data through mobile sensing, though it appears incremental as it builds on existing hardware and presents preliminary results.
The authors developed a distributed framework using mobile phone sensors to collect environmental and location data from human users, demonstrating its potential for data mining and activity classification analysis.
In this article, we present a distributed framework for collecting and analyzing environmental and location data recorded by human users (carriers) with the use of portable sensors. We demonstrate the data mining analysis potential among the recorded environmental and location variables, as well as the potential for classification analysis of human activities. We recognize that the success of such an experimental framework relies on the adoption rate by its candidate user network; thus, we have built our experimental prototype on top of hardware equipment already embedded within the potential users' everyday routine - i.e. hardware sensors installed on modern mobile phones. Finally, we present preliminary analysis results on our collected data sample, as well as potential further work directions and proposed use case scenarios.