Sociology Index

Social Networks

Social Segmentation

The term 'social network' was first coined in 1954 by J. A. Barnes. The maximum size of social networks tends to be around 150 people (Dunbar's number) and the average size around 124 (Hill and Dunbar, 2002). A social network is a social structure made of nodes which are generally individuals or organizations. It indicates the ways in which they are connected through various social familiarities ranging from casual acquaintance to close familial bonds.

Social network analysis depicts social organization or social structure in terms of patterned social relationships linking social units.

This course deals with major concepts and methods of social network analysis, touching on data collection but stressing data analysis. Some readings give applications of network approaches to selected substantive problems, but the emphasis of the seminar is on research methods.

Social network analysis takes seriously the proposition that behaviors of individual units or actors are to be understood in social context.

There are many models and methods in social network analysis, but all share a conceptualization of social structure resting on relationships of units or actors.

During the past decade, the pace of development in network studies has been very rapid. This course will introduce foundations and tried-and-true approaches to network analysis. - Social Network Analysis - - Professor Peter V. Marsden

The International Network for Social Network Analysis is the professional association of social network analysis. Started in 1977 by Barry Wellman at the University of Toronto, it now has more than 800 members and is headed by William Richards (Simon Fraser University)

Network analysis and social networks have become reasonably diverse areas involving many methodological approaches and substantive concerns. Though there is some primarily qualitative work in social networks, the bulk of it takes a quantitative angle, and this course will reflect that emphasis. Diverse elements of mathematics and statistics are used in social network analyses.
A note on focus. Network analysis is now applied within numerous substantive fields of social science.
de Nooy, Wouter, Andrej Mrvar and Vladimir Batagelj. 2005. Exploratory Social Network Analysis with Pajek. New York: Cambridge University Press.
A recent text introducing many common forms of network analysis with an emphasis on graphics/visualization. I recommend that it be read while working with the freely available network analysis software package Pajek.
Degenne, Alain and Michel Fors´┐Ż. 1999. Introducing Social Networks. Thousand Oaks, CA:
Sage Publications. (Hereafter DF.)
A more substantively and conceptually grounded, less technically oriented, introduction to network analysis.
Carrington, Peter J., John Scott, and Stanley Wasserman. 2005. Models and Methods in Social Network Analysis. New York: Cambridge University Press. (Hereafter CSW.)
A collection on recent advances in methods for studying social networks. We will be looking at most, but not all, of the chapters in CSW; some touch on statistical topics - network sampling and modeling longitudinal network data - that we will not be able to cover this term.
Watts, Duncan J. 2003. Six Degrees: The Science of a Connected Age. New York: Norton.

MB 874 - Introduction to Social Network Analysis
This course provides an intensive introduction to the field of social network analysis. The purpose of the lab is to teach you how to actually analyze social network data. This means mastering the software tools as well as analytical strategies. IMPORTANT NOTE: You will need to bring your own laptop in order to participate in the lab.
Network concepts covered will include graph-theoretic fundamentals, centrality, cohesion, subgroups, equivalence and testing hypotheses.
Required Books Software
Borgatti, S.P., Everett, M.G. and Freeman, L.C. 2002. UCINET 6 for Windows: Software for Social Network Analysis. Harvard: Analytic Technologies. Downloaded free on the network.
Wasserman and Faust. 1994. Social network Analysis. Cambridge.