This project is funded by the European Union under the Seventh Framework Programme Grant Agreement n°313082
European Union
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Social Network Analysis. Introduction to methods and applications to the EUPRO database

February 16, 2016 @ 10:30 am - February 18, 2016 @ 3:00 pm


Course objectives

This course is aims at providing participants to an introduction to different methods of Social Network Analysis and give them the tools to apply the method to their work.

The goal is to provide the participants with an understanding of the potential applicability of these methods to different types of networks and to various research questions.

The course will start with an introduction to simple descriptive methods to analyze and visualize social networks. It will then move to regression models, as widely used in spatial analysis, which try to explain the observed network characteristics from the characteristics of nodes, like their size and distance.

Finallly, the course will to introduce participants to novel statistical methods for social network analysis namely Exponential Random Graph Models, which address issues of dyadic dependence and allow analyzing network structure processes like network closure (the creation of sub-groups of nodes).

In order to demonstrate the analytical value for the research policy field, the course will include demonstrations and practical exercises done by combining the EU-PRO dataset on participation to European Framework Programs with other RISIS datasets providing data on the observed organizations, like the European Tertiary Education Register.




Programme and contents

Day 1 – February 16, 2016
10.30-11:00 Introduction
11:00-12:30 Basic concepts of social network analysis (Alessandro Lomi)
14.00 – 15.30 Introduction to network descriptive analysis (Thomas Scherngell).
15.30 – 16.15 Regression methods with examples of FP networks from the EUPRO data (Thomas Scherngell).
16.30 – 18.30 Organization of the laboratory
Day 2 – February 17, 2016
9:00-12:30 Exponential Random Graph Models (Paola Zappa)
14.00 – 18.00 Laboratory work: application of regression techniques and of ERGM to inference on network structure.
Day 3 – February 18, 2016
8.30 – 10.30. Laboratory work. Interpretation of the results and preparation of the presentations.
11.00 – 14.30 Presentations by groups.
14.30 – 15.00 Final remarks and closing of the course.


Course instructor

Prof. Alessandro Lomi, Università della Svizzera italiana
Dr. Paola Zappa, Università della Svizzera italiana
Dr. Thomas Scherngell, Austrian Institute of Technology

Audience targeted

The course aims at involving up to 15 participants among the following categories:

  • Senior scientists, early career researchers and PhDs at the last phase of their training
  • People from the policy making level wishing to extend their analytical capabilities
  • Research intermediaries (e.g. research association like Science Europe)

Requirements for participation

  • Basic knoweldge of econometrics (statistical inference, linear regressions)
  • Prior experience with network analysis is useful, no prior knowledge of ERGM required.

Organizational details

  • The course is free of charge
  • Venue of the trainees (travel and accommodation) will be covered in case of researchers, early researchers and PhDs from European countries
  • No costs are covered for people not involved in research activities (i.e. people from intermediaries or policy level)
  • Participants will be selected on the basis of interest and CV
  • Notification of acceptance will be send after the selection process is completed

Participants will be asked to send some preliminary questions about their experience with social network analysis and specific policy questions of interest

The course is organized by the Institute for Interdisciplinary Data science of the Università della Svizzera italiana ( and by the Austrian Institute of Technology (


Deadline for request participation

November 30, 2015



Paola Zappa


February 16, 2016 @ 10:30 am
February 18, 2016 @ 3:00 pm
Event Category:


Institute for Interdisciplinary Data science of the Università della Svizzera italiana and Austrian Institute of Technology


Università della Svizzera italiana
Via Buffi 13
Lugano, 6904 Switzerland
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