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Longitudinal Network Analysis with RSIENA

Five-day course, 16th to 20th September 2013 Presented by Department of Management at the University of Bologna & by School of Economics, Management and Statistics at the University of Bologna

dal 16/09/2013 alle 09:00 al 20/09/2013 alle 17:30

Dove CeUB (Bertinoro)

Contatto di riferimento

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Location:
CeUB (Bertinoro) ( http://www.ceub.it/default.asp?id=346

Instructor:
Christian Steglich ( http://www.ppsw.rug.nl/~steglich/sites/index.htm )

Content

Instructor

Venue

Fee and accommodation

Other information and contacts

Course Schedule

 


Content

The course is designed primarily for researchers who are currently doing longitudinal social network research or who are embarking upon it. More specifically, the course is about how to analyze panel data (observed at two or more discrete moments in time) on complete social networks (all the network ties within a set of actors are observed as present or absent, except a moderate amount of missing data). The course will treat the statistical modeling of the dynamics of social networks and of the co-evolution of networks and actors, according to the actor-based approach of SIENA models. Some attention will be given also to non-longitudinal network models, the so-called Exponential Random Graph Models (ERGM).

The course will cover both theoretical and practical issues and includes extensive laboratory practice with RSIENA, the implementation of SIENA models in the R environment for statistical computing. For extensive information, materials and references about the statistical analysis of social network dynamics and the SIENA approach see the SIENA website (http://www.stats.ox.ac.uk/~snijders/siena/ )

Those who are new to Social Network Analysis are advised to look at some introductory materials, such as:

-       The free online textbook on social network analysis (2005) by Robert Hanneman and Mark Riddle, Introduction to social network methods (http://faculty.ucr.edu/~hanneman/nettext/ )

-       John Scott, Social Network Analysis: A Handbook. (2nd edition). Sage, 2000

 


Instructor

Christian Steglich is a very experienced instructor of this course, which he taught many times (included two previous editions at the University of Bologna, Bertinoro Centre, in 2009 and 2011) and is still currently teaching around the world. He began his academic career under the mentorship of Tom Snijders, who first introduced this approach for the statistical modeling of social network dynamics in the late 1990s.

Christian Steglich currently works as a researcher at the ICS research school and the Faculty of Behavioral and Social Sciences of the University of Groningen. His research is mainly concerned with the formal modeling of network structure and network dynamics, with special focus on social influence processes in the context of a changing network.

 


Venue

The course is held at the Bertinoro Centre of the University of Bologna, a facility of the university located in the restored medieval castle on the top of Bertinoro, small town on the hills between Forlì and Cesena, 80 km south of Bologna.

Bertinoro Centre (http://www.ceub.it/default.asp?id=346)

Location and Directions (http://www.ceub.it/default.asp?id=435#.UQ9alfK57NI)

 


Fee and accommodation

The registration fee is 600 euro (VAT included). The fee includes course and materials, coffee breaks (morning and afternoon), internet access (WiFi and LAN). Participants are expected to bring their own laptop for laboratory practice.

Room accommodation, lunches and dinners are not included in the registration fee. Rooms are available at cheap rates inside the university facility that hosts the course (buffet breakfast and self-service lunch included in the room price). Room reservation can be done together with the course registration.

Course registration and room reservation (http://www.ceub.it/default.asp?id_c=172&id=436)

 


Other information and contacts

The maximum number of participants is 30. Other info (e.g.: for software and installation) or materials (e.g.: example data files, slides) will be given either by e-mail or at the beginning of the course.

For inquiries related to the content of the course, course materials, software ...

contact the course organizers

 

Raffaele Corrado (raffaele.corrado@unibo.it)

Simone Ferriani   (simone.ferriani@unibo.it)

 

For inquiries related to the processing of course registration, room reservation, payments …
contact the Bertinoro Centre representative

     
Roberta Partisani (rpartisani@ceub.it).

 

 


Course Schedule

 

Monday 16th

Introduction to social network analysis with R

09:00 – 11:00

Introduction to social network analysis

Coffee break

11:30 – 13:00

Getting started with network analysis in R

Lunch

14:00 – 16:00

General R features & sna package. Lab exercise

Coffee break

16:30 – 17:30

Statistical inference for social network data. Lab exercise

Tuesday 17th

Introduction to dynamic network modeling

09:00 – 11:00

Modeling network dynamics

Coffee break

11:30 – 13:00

Dynamic network visualization with the Visone software

Lunch

14:00 – 16:00

Lab exercises

Coffee break

16:30 – 17:30

Lab exercises

Wednesday 18th

Modeling the coevolution of networks and behavior

09:00 – 11:00

Model selection / goodness of fit. Lab exercise

Coffee break

11:30 – 13:00

Modeling the coevolution of networks & behaviour

Lunch

14:00 – 16:00

Lab exercises

Coffee break

16:30 – 17:30

Lab exercises

Thursday 19th

Network composition change, multilevel analyses, special topics

09:00 – 11:00

Handling composition change in networks. Different data types

Coffee break

11:30 – 13:00

Undirected networks and multiple group analyses. Lab exercises

Lunch

14:00 – 16:00

Analysis of multiplex networks. Lab exercises

Coffee break

16:30 – 17:30

Analysis of two-mode networks. Lab exercises

Friday 20th

Time heterogeneity, interaction effects,
Exponential Random Graph Models (ERGMs)

09:00 – 11:00

Testing for time heterogeneity. Lab exercise

Coffee break

11:30 – 13:00

Intercation effects and moderation. Lab exercise

Lunch

14:00 – 16:00

Exponential Random Graph Models (ERGMs)

Coffee break

16:30 – 17:30

Lab exercise on ERGMs