(Geog 5076) Network Data Analysis and Models
Tzai-Hung WEN (NTU Geography) E-mail: wenthung@ntu.edu.tw
Labs: Using R for network analysis
Lab 0. Warm up:
RMarkdown demo (點滑鼠右鍵下載
rmd file)
*
延伸教材 *
R
Markdown: Dynamic Documents for R
Lab 1.
Network data and visualization
Lab 2.
Ego-network and structure hole
Lab 3.
Centrality measures
Lab 4.
Subgroups and community detection (*
延伸教材 *
Girvan-Newman algorithm)
Lab 5. Blockmodeling and Structure Equivalence (*
延伸教材 *
CONCOR algorithm)
Lab 6. Network-level measures and two-mode networks
Labs: Network modeling with R
Lab 1. Network autocorrelation model
(* 延伸教材 *
Modeling social influence |
Structure and bias )
Lab 2. Quadratic Assignment Procedure (QAP) Regression (* 延伸教材 *
Predicting with networks )
Lab 3. Exponential Random Graph Models (ERGMs) (* 延伸教材 *
ERGMs for social networks )
Lab 4. Small-world and Scale-free network models (* 延伸教材 *
Building
network
models )
Lab 5. Network diffusion process
(* 延伸教材 *
Simulating SI diffusion |
Network modeling for epidemics )
Lab 6. Network flow model: population mobility (* 延伸教材 *
New Law of intercity mobility )
Reading Materials: Exploring the Spatial-Social Networks
Network Visualization: Spatial arrangement of social and economic networks among villages in Nang Rong District, Thailand. Social Networks 12(4): 311–337, 1999.
Ego-networks: Follow thy neighbor: connecting the social and the spatial networks on Twitter. Computers, Environment and Urban Systems (In Press, Corrected Proof, 2014).
Centrality: Centrality measures in spatial networks of urban streets. Physical Review E, 73:036125, 2006.
Subgroups: Linking cyber and physical spaces through community detection and clustering in social media feeds. Computers, Environment and Urban Systems (In Press, Corrected Proof, 2014).
Structure Equivalence: Spatializing social networks: geographies of gang rivalry, territoriality, and violence in Los Angeles. Annals of the Association of American Geographers, 100(2), 307-326, 2010.
Two-mode Networks: Mapping the evolution of hierarchical and regional tendencies in the world city network, 2000–2010, Computers, Environment and Urban Systems, 43: 51-66, 2014.
Network autocorrelation: Spatializing the social networks of gangs to explore patterns of violence. Journal of Quantitative Criminology 27(4): 521-545, 2011.
QAP Regression: Social context, spatial structure and social network structure. Social Networks 34(1): 32-46, 2012.
Exponential Random Graph Models: Regional geographies of intercity corporate networks: The use of exponential random graph models to assess regional network‐formation. Papers in Regional Science 94(1): 109–126, 2015.
Small-world network: Small-world characteristics on transportation networks: a perspective from network autocorrelation. Journal of Geographical Systems 9(2): 189-205, 2007.
Network diffusion process: Spatial knowledge diffusion through collaborative networks. Papers in Regional Science 86 (3): 341–350, 2007.
Network flow model: A universal model for mobility and migration patterns. Nature 484:96–100, 2012.