Events at The University of Manchester
  • University home
  • Events
  • Home
  • Exhibitions
  • Conferences
  • Lectures and seminars
  • Performances
  • Events for prospective students
  • Sustainability events
  • Family events
  • All Events

methods@manchester Summer School: Statistical analysis of social networks

image
Dates:3 July 2017 - 7 July 2017
Times:All day
What is it:Course
Organiser:methods@manchester
How much:£600 - students and University of Manchester staff; £900 - others
Who is it for:University staff, Adults, Alumni, Current University students, General public
Speaker:Johan Koskinen
See travel and contact information
Add to your calendar

More information

  • Booking
  • methods@manchester website

Other events

  • In category "Course"
  • By methods@manchester

Summary

This is an introduction to statistical analysis of networks. While no strict prerequisites are assumed, you might find it helpful to have some basic knowledge of social network analysis beforehand. To benefit fully from the course requires a basic knowledge of standard statistical methods, such regression analysis. The course aims to give a basic understanding of and working handle on drawing inference for structure and attributes, both cross-sectionally as well as longitudinally. A fundamental notion of the course will be how the structure of observed graphs relate to various forms of random graphs. This will be developed in the context of non-parametric approaches and elaborated to analysis of networks using exponential random graph models (ERGM) and stochastic actor-oriented models. The main focus will be on explaining structure but an outlook to explaining individual-level outcomes will be provided.

The participant will be provided with several hands-on exercises, applying the approaches to a suite of real world data sets. We will use the stand-alone graphical user interface package MPNet and R. In R we will learn how to use the packages ‘sna’, ‘statnet’, and ‘RSiena’. No familiarity with R is assumed but preparatory exercises will be provided ahead of the course.

Literature we will draw on includes:

Lusher, D., Koskinen, J., Robins, G., (2013). Exponential Random Graph Models for Social Networks: Theory, Methods and Applications, Cambridge University Press, NY.

Snijders, Tom A. B., Gerhard G. van de Bunt, and Christian E.G. Steglich. 2010. “Introduction to stochastic actor-based models for network dynamics.” Social Networks 32:44-60.

MPNet can be downloaded from MelNet

Course objectives

The course will:

Introduce how statistical evidence relates to social networks Explain how to draw inference about key network mechanisms from observations Provide hands-on training to use software to investigate social network structure tie-formation in cross-sectional data tie-formation in longitudinal data take into account network dependencies between individuals Course timetable

Day one

Introduction to working with networks in R

Day two

Morning – Subgraphs and null distributions and ERGM rationale

Afternoon – ERGMs and dependence

Day three

Morning – ERGM: Issues and technicalities

Afternoon – SAOM: introduction to longitudinal modelling

Day four

Morning – SAOM: introduction to longitudinal modelling

Afternoon – Extensions and further issues

Day five

Morning – Influence, contagion, and outlook to further issues.

Timetable is subject to change.

Course tutors

The course will be taught by Dr Johan Koskinen

Booking

Booking is now open for the Summer School 2017.

To pay be credit card please visit our e-store

To pay by invoice (institutions only) please complete the booking form on the methods@manchester website and email a copy of a Purchase Order to methods@manchester.ac.uk

If you are based at the University of Manchester and your fee is being paid by your department please complete the booking form and contact us to arrange an internal journal transfer.

Price: £600 - students and University of Manchester staff; £900 - others

Speaker

Johan Koskinen

Role: Lecturer in Social Statistics

Organisation: University of Manchester

  • https://www.research.manchester.ac.uk/portal/Johan.Koskinen.html

Travel and Contact Information

Find event

Humanities Bridgeford Street
Manchester

Contact event

Mark Kelly

0161 275 0796

mark.kelly@manchester.ac.uk

Contact us

  • +44 (0) 161 306 6000

Find us

The University of Manchester
Oxford Rd
Manchester
M13 9PL
UK

Connect with the University

  • Facebook page for The University of Manchester
  • X (formerly Twitter) page for The University of Manchester
  • YouTube page for The University of Manchester
  • Instagram page for The University of Manchester
  • TikTok page for The University of Manchester
  • LinkedIn page for The University of Manchester

  • Privacy /
  • Copyright notice /
  • Accessibility /
  • Freedom of information /
  • Charitable status /
  • Royal Charter Number: RC000797
  • Close menu
  • Home
    • Featured events
    • Today's events
    • The Whitworth events
    • Manchester Museum events
    • Jodrell Bank Discovery Centre events
    • Martin Harris Centre events
    • The John Rylands Library events
    • Exhibitions
    • Conferences
    • Lectures and seminars
    • Performances
    • Events for prospective students
    • Sustainability events
    • Family events
    • All events