From Geo-Social to Geo-Local: The Flows and Biases of Volunteered Geographic Information

Abstract

This dissertation analyzes the geography of information in the 21st century where BigData, social networks, user generated production of content and geography combine to create new and complex patterns of space, context and sociability. Both online and offline, social networks are creating a space that simultaneously unifies individuals and identifies distinct differences in their patterns and their relationships to space. Using methodologies derived from spatial analysis, geographic information systems (GIS), and Social Network Analysis (SNA), this dissertation identifies how Information Communication Technologies (ICTs) both mimic and bolster existing social structures and allow individuals to extend their activities into flows between non-contiguous spaces. Simultaneously it demonstrates how the adoption of user-generated geographic information has not been uniform. Instead it has resulted in an uneven distribution of content and more nuanced digital divides. Although geographically uneven, social structures developed through online networks of user-generated content are most effective at transmitting information at a local level. This dissertation provides a comprehensive examination of online networks and representations of the GeoWeb. It repudiates previous assumptions that online content provides liberation and collaboration among users without regard to geographic constraints and demonstrates the locally constrained nature social networks and the demographically constrained nature of geographic information.