After the success of three Editions of the Workshop "Introduction to Social Network Analysis", the Department of Political Science of the University of Pisa is now organizing an International Summer School on "Methods for Social Network Analysis with R".
The Summer School helps participants who are in the midst of an SNA research project or engaged in analyzing network data for an earlier study. We will briefly discuss how to create a rendering of the participants’ work that increases the power of their analysis, using the most recent and powerful tools offered by software packages such as "Statnet".
The following will be the area covered in the Summer School:
- Introduction to Networks
- Why network analysis?
- How is it different from other methods?
- Some history
- Introduction to the R computing environment
- How do we talk about networks?
- Node, neighborhood, and network-level statistics
- Hypothesis testing
- How do we take the descriptives and start to develop hypotheses at the node, neighborhood and network level?
- QAP tests
- Network autocorrelation models
- Conditional Uniform Random Graph tests
- Introduction to Exponential Random Graph Models Extensions of ERGM and individual presentations
- Valued models
- Temporal models
- Multiplex networks
- Comparing multiple networks
It will be a five-day, intensive course mainly devoted to introducing participants to Social Network Analysis with a practical approach, and with the aim to giving answer to questions such as “how to do research”, “how to collect, analyze and interpret social network data data”, using the "R" environment, especially the package "Statnet".
Join us at the Summer School and be an active learner in our classes and in our collaborative groups. Meet interesting people with whom you can interact and discuss topics of your own interest concerning SNA methods and how to give the answer to your daily research problems.
Attending the International Summer School on "Methods for Social Network Analysis with R", students become members of a scientific community based on the continuous exchange and comparison between knowledge and experience. This course will begin with a brief introduction to networks and the R programming language (day 1) and then move into a variety of descriptive methods with examples of how these have been used in a variety of social science kinds of literature (day 2). The focus of the next two days will be how to develop questions about social networks in the socio-environmental context and appropriately test them with extensions of standard regression models (day 3) and exponential random graph models (day 4). Participants are encouraged to bring their own data to the course. We will have some independent time each day to try to apply the concepts learned to each dataset. For those without data on hand, the instructor will be able to help you find (an) interesting dataset(s) that you can play with during the course. We will try and keep the final part of the afternoon of each day for students to work on their own to adapt the day’s material for their own dataset. The final day (5) will be used for more advanced methods depending on the interests of the participants and also for students to present their own work during the week as well as any networks related research ideas.
Who can apply
Undergraduate and Postgraduate students, Ph.D. candidates, professors, researchers, professionals operating both in public and in private fields.
No admission requirements.
- Identity Document (*PASSPORT in case you are a foreign student*)
- Enrolment Form
- Curriculum Vitae
All the documents must be in pdf format, in order to upload them on the portal when required (See the "How to apply" page)
Please write to the coordinator for further details.
20 - 24 April 2020
31 March 2020
About the School
The University of Pisa is a public institution boasting twenty departments, with high level research centres in the sectors of agriculture, astrophysics, computer science, engineering, medicine and ve ... Read More