Estimating Individual Behaviour for Massive Social Data
Malleson, Nicholas and Birkin, Mark (2013) Estimating Individual Behaviour for Massive Social Data. In: Geosimulation: Modeling Social Phenomena in Spatial Context. LIT Verlag, pp. 23-29. ISBN 978-3-643-90345-7
Full text not available from this repository.Abstract
This chapter presents the most recent developments in an on-going programme of work towards a
realistic agent-based model of urban dynamics. The focus of the chapter is on the development of
a framework for calibrating an agent-based model of urban dynamics using novel data from the
Twitter social media service. In particular, we discuss initial attempts to elucidate information
about peoples' daily spatio-temporal behaviour and how such insight can be used for the bene�t of
agent-based models. The ultimate aim of the modelling work is to better understand the spatio-
temporal movement patterns within the city.
Item Type: | Book Section |
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Subjects: | 5. Quantitative Data Handling and Data Analysis > 5.9 Spatial Data Analysis |
Depositing User: | TALIS User |
Date Deposited: | 25 Jun 2013 10:04 |
Last Modified: | 14 Jul 2021 13:58 |
URI: | https://eprints.ncrm.ac.uk/id/eprint/3129 |