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- W2141640485 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." @default.
- W2141640485 created "2016-06-24" @default.
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- W2141640485 date "2013-11-18" @default.
- W2141640485 modified "2023-09-24" @default.
- W2141640485 title "Modeling Use of Space from Social Media Data Using a Biased Random Walker" @default.
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- W2141640485 doi "https://doi.org/10.1111/tgis.12069" @default.
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