Modeling Use of Space from Social Media Data Using a Biased Random Walker

Abstract

Individuals and other entities move through space as a function of local characteristics of place, their internal behavioral models, and the topological structure of the underlying space. When a collection of locations (i.e. geotagged photos or other geotagged social media information) from a large number of individuals is assembled, it becomes possible to understand the interrelationship between the individuals and the space they occupy. This research systematically considers this interrelationship through an examination of the effect of the intersection of behavioral and spatial characteristics on individuals moving on street networks. The research illustrates how social media data, in combination with a biased random walker, can be used to understand and model the interaction of spatial structure and social‐environmental factors on influencing individuals' use of their environment. The biased walker offers a flexible approach to incorporate consideration of both social‐environmental and structural factors into a model and we demonstrate this through a case study wherein we are able to use the random walker to model the characteristics of Flickr users in New York City.

Document Details

Document Type
Pub Defense Publication
Publication Date
Nov 18, 2013
Source ID
10.1111/tgis.12069

Entities

People

  • R. Paul Wiegand
  • Steven D. Prager

Organizations

  • National Geospatial-Intelligence Agency
  • University of Central Florida
  • University of Wyoming

Tags

Readers

  • Agent-Based Social Robotics and Mobile-Assisted Learning in Virtual Environments.
  • Microwave Engineering.
  • Regression Analysis.

Technology Areas

  • Space