A Proposed Framework for Crowd-Sourced Social Network Data Collected over Bluetooth
MetadataShow full item record
Currently, mobile computing is mandating or influencing the direction of new developments in information technology. The high level of adoption that mobile devices have among individuals allows for multiple opportunities for new developments applicable to academic communities, governments and businesses. Data of various types can be collected in a crowd-sourced manner. As such, this thesis examines the collection and application of data collected through a purpose-designed app relying on Bluetooth and geo-location technologies on mobile devices. Through three distinct development iterations and using Bluetooth connectivity, information about connectivity to other mobile devices can be obtained, and in this way the number, type, and device names of “connecting” devices are gathered and stored. Another interesting aspect associated with this type of data collection is that the mobile device may be either moving or stationary during the data collection process. Information can be collected and mined to help map real-life events such as traffic patterns or crowd movement within mass gatherings, as well as ethereal social interactions, and these data can in turn be used as input to various models and simulators. When geo-location technologies are incorporated, a higher level of detail can be obtained on the location of devices. This technology allows for mapping movement and contacts made between people, allowing for the gathering of more detailed social patterns of individuals. As part of this study, the technology developed using Bluetooth connectivity and geo-location is then taken to an additional iteration to develop a mobile system that is able to find and establish direct connections with other individuals and initiate real-life interactions. The work demonstrates that mobile technologies can provide a broad framework of action for the generation and collection of valuable data that can be used for behavioural studies, simulations and other type of research that involves real-life social interactions.