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How to analyze networks with RExport this event to calendar

Wednesday, April 10, 2019 (all day) to Thursday, April 11, 2019 (all day)

In this two-day workshop, you will learn a variety of tools for analyzing data on social and information networks using the programming language R. The first day will be an introduction to R and RStudio, followed by a series of classic topics in network analysis, such as centrality analysis and community detection. The second day will cover visualization, handling extremely dense networks, and developing statistical models for network data. 

The workshop sessions will combine short lectures and demonstrations with hands-on time analyzing your own (or our) network data. 

DAY 1

  1. Introduction: what is distinctive about research on social and / or information networks?
  2. Why R? A brief introduction to R and RStudio 
  3. From raw data to networks: getting your data into R and ready for iGraphsna, and statnet 
  4. Analyzing centrality and brokerage
  5. Detecting cohesive subgroups / communities 
  6. Block models 

DAY 2

  1. Visualizing networks with ggnet 
  2. Dealing with extremely dense networks: edge thresholds vs. extracting the network backbone
  3. Statistical models for networks: An introduction to Exponential Random Graph Models (ERGMs)
  4. Developing and interpreting ERGMs

Software and Assumed Background


This workshop makes extensive use of the programming language R, including the libraries iGraph, statnet, and ggnet.

Although having some knowledge of R is an asset, it is not required. I will provide all participants with fully executable code for all topics covered in the workshop. Participants will be encouraged to modify the code to suit their specific interests, but this requires minimal programming knowledge and is not required. If you want to learn a bit of R before the workshop, we highly recommend selecting something from DataCamp.

Participants will be provided with detailed instructions of what software to install and how to install it a couple of weeks before the start of the workshop.
 

Register for the Workshop 

To register for the workshop, please complete this short form. Please note that if you register for more than one workshop, you will need to process each registration separately. 

Space is limited, so we encourage you to register as soon as possible. 

Instructor & Workshop Organizer

John McLeveyJohn McLevey is an Assistant Professor in the Department of Knowledge Integration (Faculty of Environment) at the University of Waterloo. He is the Principal Investigator of a computational social science and social networks research lab called NETLAB, which is funded by grants from the Social Sciences and Humanities Research Council of Canada and an Early Researcher Award from the Ontario Ministry of Research and Innovation. 

John primarily works in the areas of computational social science and social network analysis, with substantive interests in environmental social science, the sociology of science, social movements, and cognitive social science. As a computational social scientist, his most general research goal is to advance our knowledge of how social networks and institutions affect collective cognition and behaviour, including the formation and diffusion of knowledge, beliefs, biases, and behaviours. He is currently involved in a number of research projects in service of that larger goal, including work on the effects of cognitive diversity and homophily in scientific networks, environmental governance conflicts in coastal regions, mobilization into environmental activism, and the diffusion of educational innovations. He is currently writing a book on computational social science for Sage's research methods series. 

Partners

This workshop is held in partnership with the Department of Knowledge Integration, the Faculty of Environment at the University of Waterloo, and NETLAB

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Food and Accomodations 

Coffee, tea, and snacks will be provided during the workshop. There are a variety of options for lunch and dinner on campus or within a short walk from campus. 

We will follow up with travelling participants about options for local accomodations. 

Cost 
$400 CAD, $200 CAD for students
Location 
EV1 - Environment 1
TBA
200 University Ave West
Waterloo, ON N2L 3G1
Canada

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  1. 2019 (3)
    1. April (3)