Introduction to Social Network Analysis Using UCINET and Netdraw



PARK AVENUE Hotel, Sungai Petani, Kedah


5 – 6 November 2017


08:30 to 17:00


Organized by:

The 3rd International Conference on Computing, Mathematics and Statistics (iCMS2017), UiTM Kedah


Trainer and Facilitator: Professor Martin Everett (University of Manchester, Manchester, UK)


Professor Martin Everett joined the University of Manchester in 2009 having previously worked at East London, Westminster and Greenwich universities. He has helped cofound the Mitchell Centre for Social Network Analysis which evolved from the existing Manchester Social Networks Group. He is a past president of the International Network for Social Network Analysis (INSNA) and a Simmel award holder (the highest award given by the organization). He was elected an academician of the Academy of Social Sciences in 2004. Professor Everett co-author with Steve Borgatti in the development of the software package UCINET, the world’s most commonly used software for analyzing social network data. He has been consulted extensively on the use of networks with government agencies as well as public and private companies. He has co-authored two books and published over 80 journal articles. Professor Everett is also the co-editor of the journal Social Networks. The Impact Factor of the journal is 2.784 with 5-Year Impact Factor of 4.113, and SCImago Journal Rank (SJR) of 2.070.



What is Social Network Analysis (SNA)?

The social network is a theoretical construct useful in the social sciences to study relationships between individuals, groups, organizations, or even entire societies (social units, see differentiation). An axiom of the social network approach to understanding social interaction is that social phenomena should be primarily conceived and investigated through the properties of relations between and within units, instead of the properties of these units themselves. Network analytics are useful to a broad range of research enterprises. In social science, these fields of study include, but are not limited to anthropology, biology, communication studies, economics, geography, information science, organizational studies, social psychology, sociology, and sociolinguistics.



A sociogram generated by UCINET



Course content overview

This is an introductory course, covering the concepts, methods and data analysis techniques of social network analysis. The course is based on the book "Analyzing Social Networks" by Borgatti et al. (Sage) and participants would find it useful to have a copy of the book (but this is not essential). The course begins with a general introduction to the distinct goals and perspectives of social network analysis, followed by a practical discussion of network data, covering issues of collection, validity, visualization, and mathematical/computer representation. We then take up the methods of detection and description of structural properties, such as centrality, cohesion, subgroups and positional analysis techniques. This is a hands on course largely based around the use of UCINET software, and will give participants experience of analyzing real social network data using the techniques covered in the workshop. No prior knowledge of social network analysis is assumed for this course.


Course objectives

The course will,

Introduce the idea of Social Network Analysis.

Explain how to describe and visualize networks using specialist software (UCINET).

Explain key concepts of Social Network Analysis (e.g. Cohesion, Brokerage).

Provide hands-on training to use software to investigate social network structure.


Prior or recommended knowledge/reading/skills

None required but it would be useful to read Scott J (2000) Social Network Analysis: A handbook. Sage.


Software to be used

UCINET and Netdraw. It is useful for participants to bring their own laptops running windows (Macs will need to have a pc emulator) and to have downloaded the software in advance. This can be done for a free period of time from the website


Workshop Schedule




Book chapter

Day 1


1) Introduction to SNA, terminology and the software UCINET/Netdraw.

Chapters 1 & 2


2) Collecting Social Network Data and  Research Design

Chapters 3 & 4


Day 1


Data management and Visualization.

Chapters 5 and 7


Multivariate techniques and whole networks.

Chapters 6 and 9


Day 2


Centrality and Ego networks.

Chapters 10 and 15


Equivalence and core-periphery.

Chapter 12


Day 2


Subgroups and two-mode networks.

Chapters 11 and 13


Testing hypothesis and Large networks.

Chapters 8 and 14


To register, please go to the registration page