By Michał
I would like to (re)announce the workshop I will be giving on using R and ‘igraph’ for Social Network Analysis on the upcoming Sunbelt 2016 conference in Newport Beach. My goal is to provide gentle and practical tour through the SNA functionality of R package “igraph”. The exact date of the Sunbelt workshop is Tuesday April 5th, 8:00am – 2:30pm. Consult the Sunbelt workshop program or further details.
Do note that March 7 is the deadline for Sunbelt workshop registrations!
If you are not attending Sunbelt I will be very happy to meet you on the workshop at the European Social Networks Conference (EUSN 2016) which will take place in Paris (14-17th of June, 2016), see http://eusn2016.sciencesconf.org/84811 for further details.
See the bottom of this post for some more details on the workshop.
I hope to see you on Sunbelt or EUSN!
As a side note, on EUSN I will be also co-teaching two ‘statnet’ workshops which will be announced separately.
Using R and igraph for Social Network Analysis
The workshop introduces R and package igraph for social network data manipulation, isualization, and analysis. Package igraph is a collection of efficient tools for storing, manipulating, visualizing, and analyzing network data. Igraph is in part an alternative, in part a complement to other SNA-related R packages (e.g. statnet, tnet). It is an alternative as it goes for network data manipulation and visualization. It is a complement because of a large and growing collection of algorithms, including community detection problems, unavailable elsewhere. The material will cover:
- Brief introduction to R.
- Creating and manipulating network data objects.
- Working with node and tie attributes.
- Creating network visualizations.
- A tour through computing selected SNA methods including: degree distribution, centrality measures, shortest paths, connected components, quantifying homophily/segregation, network community detection.
- Connections to other R packages for SNA, e.g.: statnet, RSiena, egonetR.
The focus is on analysis of complete network data …read more
Source:: r-bloggers.com