This course deals with emerging applications and methodological advances in social network analysis. It revises and builds on the frameworks for social network research and network analysis used in the introductory ACSPRI course: Introduction to Social Network Research and Network Analysis.
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.
This second level course explores the maximum capabilities and limits of the UCINET/NetDraw software used in the introductory course and charts paths of transition to other software for data collection (ONASurvey), visualisation (NodeXL. Pajek, Visione) and R programs for network data analysis and ergm (igraph and statnet). It considers the typical issues encountered when dealing with ‘big data’ (administratively generated data of flows and exchange), electronic communications (email records) and social media data (Facebook, Twitter). The course structure allows for discussion and exploration of datasets and problems brought to the course by participants.
Session 1.1: Introductions, overview and scoping
Session 1.2: Data formats for network data and social network datasets
Session 1.3: Network visualisation packages: A survey and recommendations
Session 1.4: Core elements of network analysis and social research using network data
Session 2.1: Scaling up: The limits and limitations of UCINET
Session 2.2: Data analysis in Pajek
Session 2.3: Network packages in R: igraph, sna and StatNet
Session 2.4: SNA in R: The standard datasets and examples
Session 3.1 and 3.2: SNA in R: Big datasets
Session 3.3 and 3.4: The special world of social media data
Session 4.1: Social network research and network science
Session 4.2: The new horizons of social network research
The remaining time will be devoted to individual consultations, work and collective discussion of projects nominated by attendees.
This course is run in a computer lab. Equipment will be provided.
The ACSPRI course, Introduction to Social Network Research and Network Analysis.
The new web-based resources were very helpful. Excellent format for participatory classwork & individual work. (Winter 2014)
The course presented practical applicable information as well as theoretic grounding. Big picture concepts alongside introductions to software and structuring data, design, methods. (Winter 2014)
The instructor's bound, book length course notes will serve as the course texts.