Introduction to Social Network Research and Network Analysis

This course introduces information and data collection methods used by social scientists working on social networks. It familiarises participants with the principal software packages used in social network analysis (UCINET and Pajek) and provides hands-on experience of working with these packages. Participants will carry out a small network project of their own to develop a real familiarity with methods and techniques of social network research and data analysis.
Monday am: Overview and scoping of the course; Collecting sociometric data; Collecting 2-mode data.
Monday pm: Introduction to UCINET (and NetDraw); data entry formats (VNA standard); Layouts for network visualisation; Colours and shapes. Drawing complex network diagrams.
Tuesday am: Data organisation and management; Exporting from Excel or Access to UCINET; Data sources for network analysis.
Tuesday pm: Complex network diagrams (extension); Dealing with large datasets; Visualisation and its limits.
Wednesday am: Varieties of social network research; the sociometric legacies; ego network studies, sample surveys and network analysis.
Wednesday pm: Random graphs and geodesics (‘small world’ network architecture); exploring large datasets with visualisations.
Thursday am: Personal networks and community studies; Probability samples and networks (including ‘small world’ studies and 2-mode data).
Thursday pm: Using SNA metrics to explore large (random) graphs.
Friday am: Scientific interest in networks, how does it relate to social network analysis. (Plus consultations with the instructor.)
Friday pm: Mini-conference: Participants present a short account of the particular project they have worked on through the course.
Participant project templates:
Participants can choose a small project from the following types of study:
Sociometric data in bounded groups; Mapping personal (ego) networks; Participation in community organisations (Volunteering); Geodesic paths in ‘small world’ networks; Event attendance and clique formation.

Level 1 - runs over 5 days

Associate Prof Malcolm Alexander is one of Australia’s leading sociologists working in the area of social network analysis and mathematical sociology. He made intensive studies of Australian business elite networks of the 1990s directed to public issues of corporate governance and investor capitalism. In recent years he has developed network analysis in new directions through his focus on 2-mode network mapping and investigations of elite networks in the civic cultures of Australian cities. He has published numerous articles in sociological journals, is the editor of two books and was also an editorial member of the Journal of Sociology and executive member and Treasurer of The Australian Sociological Association.

Course dates: Monday 14 January 2013 - Friday 18 January 2013
Course status: Course completed (no new applicants)
Week 1
Recommended Background: 

No prior knowledge of social networks analysis is required. Participants should be comfortable with using spreadsheets (Excel) and have some social science background.

Recommended Texts: 

Scott, J. (2000). Social network analysis : a handbook. London ; Newbury Park, Calif., SAGE Publications.
Buchanan, M. (2002). Nexus : small worlds and the groundbreaking science of networks. New York, W.W. Norton.
Borgatti, S. P., M. G. Everett, et al. (2002). Ucinet 6 for Windows: Software for social network analysis. Harvard, Analytic Technologies. Manual; User Guide.
Pajek: Program for Large Network Analysis: at
Nooy, W. d., A. Mrvar, et al. (2005). Exploratory social network analysis with Pajek. New York, Cambridge University Press

Course fees
Non Member: 
Full time student Member: 

Notes are provided throughout course.