Title
A Framework for Generating Geospatial Social Computing Environments
Abstract
Computational social science plays an important role in emergency management from a quantitative perspective. Reconstructing an individual-based social computing environment is crucial for both accurate computational experiments and determining optimal decisions. Here, the authors propose a formalization method to define basic componential models in the artificial society and the inner logic in these models. A detailed generation process is presented, and multisource statistical data, social interactive behavior, and multilayer social networks are integrated together. As an evaluation of the proposed framework, a virtual city of Beijing is reconstructed. Each citizen is endowed with demographic attributes, including age, gender, social role, correlated geographic locations, and multiple social relations. The generated synthetic population is statistically equivalent to the real population. Transmission experiments of influenza are performed in the reconstructed computational environment, and individual daily interacting behavior is tracked and analyzed. The results indicate that the framework can provide an effective methodology to reconstruct the computing environment in high resolution by using low-resolution statistical data, leading to better prediction and management of emergencies.
Year
DOI
Venue
2015
10.1109/MIS.2014.34
IEEE Intelligent Systems
Keywords
Field
DocType
individual-based modeling,virtual city,multilayer social networks,emergency management,low-resolution statistical data,social interactive behavior,formalization method,geography,geospatial environment,synthetic population,intelligent systems,individual-based social computing environment,multisource statistical data,artificial society,social sciences computing,geospatial social computing environments,schedules,statistics,sociology,computational modeling
Social relation,Data science,Geospatial analysis,Population,Social network,Intelligent decision support system,Computer science,Knowledge management,Computational sociology,Artificial society,Social computing
Journal
Volume
Issue
ISSN
30
1
1541-1672
Citations 
PageRank 
References 
7
0.53
3
Authors
5
Name
Order
Citations
PageRank
Rongqing Meng1122.38
Yuanzheng Ge2213.53
ZhiDong Cao36715.12
Xiaogang Qiu414920.35
Kedi Huang57911.95