Workshop in the MIDST: Complex networks analysis in R with applicatio...13-06-2019
Speaker: Güven Demirel
Affiliation: Queen Mary University of London, School of Business and Management
Date: Thursday, June 20, 2019
Location: FENS (Faculty of Engineering and Natural Sciences) G055, Sabanci University, İstanbul
Title: Complex networks analysis in R with applications to supply chain management and ecology
Abstract: This workshop will provide a brief introduction to complex networks analysis using the R programming language. The theory session will start with establishing the basics of computation in R, including data structures, operators, functions, control structures, loop functions, and data importing and exporting. The session will continue with defining, manipulating, visualizing, and analyzing complex networks in R. We will create networks from empirical data as well as from models such as preferential attachment model, small-world model, exponential random graph models, and stochastic block models.
We will compute and visualize different centrality metrics, measures of cohesion, and community structure. In the hands-on session, we will first compute and visualize descriptive network statistics for an empirical supply network from Choi and Hong (2002). We will then generate and analyze ecological networks from empirical data as well as the niche model (see Allesina et al. (2015) and references therein). No prior knowledge of R or complex networks theory is required. We kindly ask you to bring your laptops and recommend installing R (https://www.r-project.org/) and R Studio (https://www.rstudio.com/) prior to the workshop.
This workshop is delivered in the scope of the "Resilience of supply networks: An “interdependent complex networks approach" project funded by the British Academy Newton Mobility Grant NMG2R2\100183.
Allesina, S., Grilli, J., Barabás, G., Tang, S., J. Aljadeff, and A. Maritan. 2015. "Predicting the stability of large structured food webs." Nature Communications 6: 7842
Choi, T. Y, and Y. Hong. 2002. “Unveiling the Structure of Supply Networks: Case Studies in Honda, Acura, and Daimler–Chrysler.” Journal of Operations Management 20 (5): 469–93.
Kolaczky, E. D. D., & D.R. Csardi (2014). Statistical Analysis of Network Data with R. Springer. Luke, D. A. (2015). A User’s Guide to Network Analysis in R. Springer.
Newman, M. E. J. (2003). The structure and function of complex networks. SIAM Review, 45, 167–256.
Ognyanova, K. 2016. “Network Analysis and Visualization with R and Igraph.” NetSciX 2016 School of Code Workshop, Wroclaw, Poland: //www.kateto.net.
Dr Güven Demirel is Lecturer in Supply Chain Management at the School of Business and Management, Queen Mary University of London, United Kingdom. He holds a PhD in Physics from the Technical University of Dresden, Germany. He previously worked at the Max Planck Institute for the Physics of Complex Systems, Dresden, Germany; Nottingham University Business School, UK and Essex Business School, UK. He conducts interdisciplinary research on complex systems, investigating the stability and resilience of supply networks and ecological networks; the effectiveness of supplier development programs; and the co-evolution of the network structure and contact processes. He is the author of research articles in prestigious journals, including Science, Physica D, Journal of Operations Management, and European Journal of Operational Research.