Cost

This is a paid course costing £215. Please register your interest via EventBrite, and we will be in touch with details of how to book, and bursaries for PhD students.

Overview

The course will cover:

• general introduction to the distinct goals and perspectives of social network analysis
• practical discussion of network data, covering issues of collection, validity, visualization, and mathematical/computer representation
• detection and description of structural properties, such as centrality, cohesion, subgroups and positional analysis techniques.

We will consider how to:

• describe and visualise networks using specialist software (UCINET).
• use the key concepts of Social Network Analysis (e.g. Cohesion, Brokerage).
• use software to investigate social network structure.

By the end of the course you will be able to use UCINET software, and gain some experience of analyzing real social network data.

Prerequisites

No prior knowledge of social network analysis is assumed for this course. However, it would be useful to read Scott's (2000) Social Network Analysis: A Handbook.

Participants are required to:

• obtain a copy of Analyzing Social Networks by Borgatti et al. (2018), which will be used throughout the course. The cost of the book has been deducted from the course fee (normally £240) to allow participant to purchase the text.
• download the UCINET and Netdraw software packages in advance. This can be done for a free period of time from the Analytictech website. It is useful for participants to have a PC running windows; Macs will need to have a PC emulator.

Course timetable

Monday 28th June

Afternoon: Introduction to social network analysis, terminology and the software UCINET/Netdraw (Borgatti et al. (2018), Chapters 1 and 2).

Tuesday 29th June

Morning: Collecting social network data and research design (Chapters 3 and 4).

Afternoon: Data management and visualisation (Chapters 5 and 7).

Wednesday 30th June

Morning: Multivariate techniques and whole networks (Chapters 6 and 9).

Afternoon: Centrality and ego networks (Chapters 10 and 15).

Thursday 1st July

Morning: Equivalence and core-periphery (Chapter 12).

Afternoon: Subgroups and two-mode networks (Chapters 11 and 13).

Friday 2nd July

Morning: Testing hypothesis and large networks (Chapters 8 and 14).

Course leaders

Elisa Bellotti is a Senior Lecturer at The University of Manchester. Along with being part of the Sociology department, she is a member of the Mitchell Centre for Social Network Analysis, where she organises the weekly seminar series. She teaches introductory and advanced workshops in social network analysis and egonetworks, and in mixed methods in SNA. Before arriving in Manchester in 2008, she worked as a research fellow at the University of Turin and the University of Bozen, Italy. She completed her PhD in Sociology and Methodology of Social Research in 2006 at Catholic University of Milan. Her research interests mainly focus on relational sociology and its link with other mainstream sociological theories; and on social network analysis and mixed methods. She has taken this approach in several sociological substantive areas, such as the study of intimacy and personal relationships, sociology of science, criminal networks, inter and intra organisational ties, and sociology of consumption.

Nick Crossley is Professor of Sociology at The University of Manchester. His main work using social network analysis has focused upon music worlds, social movements and covert networks. He has also written extensively about 'relational sociology', a theoretical position that advocates a focus upon networks in sociology. His most recent book is Networks of Sound, Style and Subversion: the Punk and Post-Punk Worlds of Manchester, London, Liverpool and Sheffield, 1975-1976 (Manchester University Press).

Martin Everett is a Professor in Social Network Analysis at the University of Manchester and currently co-directs the Mitchell Centre for Social Network Analysis (with Nick Crossley). He has been a past president of the International Network for Social Network Analysis (INSNA) and is co-author of the software package UCINET and the Sage book Analyzing social networks. Martin regularly gives invited talks at major conferences and is co-editor of the journal Social Networks. He is a fellow of the Academy of Social Sciences and a Simmel award holder, the highest honour given by INSNA.