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
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

Actions (login required)

View Item
View Item