Note: this course was previously called "Introduction to Social Network Research and Network Analysis"
This course covers data collection methods, measures, indicies, simulations and statistical modeling used by social scientists studying social networks. It familiarises participants with the principal visualisation and software packages used in social network analysis; UCINET/NetDraw (Pajek, NodeXL, Gephi)and PNet (StOCNet, Statnet) and provides hands-on experience of working with UCINET and PNet. 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.
It is unclear if this course will take place in a computer lab or using laptops. If the latter, ACSPRI will provide instructions and other help to ensure you have access to a suitable laptop in advance of the course.
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.
No prior knowledge of social networks analysis is required. Participants should be comfortable with using spreadsheets (Excel) and have some social science background.
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. www.analytictech.com
Borgatti, S. P., M. G. Everett, et al. (2013). Analyzing social networks, Sage.
PNet: http://sna.unimelb.edu.au/PNet
Robins, G. (2015). Doing Social Network Research: Network-based Research Design for Social Scientists, Sage.
Notes are provided throughout course.