methods@manchester summer school 2019 - Advanced Social Network Analysis
Date:
08/07/2019 - 12/07/2019
Organised by:
methods@manchester
Presenter:
Dr Termeh Shafie
Dr David Schoch
Prof. Martin Everett
Level:
Advanced (specialised prior knowledge)
Contact:
methods@manchester
email: methods@manchester.ac.uk
telephone: 01612754269
Description:
Overview
An introduction to statistical analysis of networks and some advanced concepts building on the introductory course. 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 for cross-sectional data. 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 permutation tests. 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 and R as well as other specialist SNA software (Visone and UCINET.) In R we will learn how to use the packages ‘SNA’ and ‘statnet’. No familiarity with R is assumed but preparatory exercises will be provided ahead of the course.
Course objectives
The course will:
· Examine advanced descriptive concepts
· Discuss how to handle missing data
· 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 and take into account network dependencies between individuals
Prior or recommended knowledge/reading/skills
A basic knowledge of standard statistical methods
Cost:
Cost - Students - £600
University of Manchester Staff - £600
Other attendees - £900
Website and registration:
https://www.methods.manchester.ac.uk/connect/events/summer-school-2019/
Region:
North West
Keywords:
Social Network Analysis, Quantitative Software, R, Visone and UCINET
Related publications and presentations:
Social Network Analysis
Quantitative Software
R