Network Analysis I: Introduction


  • Ann McCranie, Indiana University

This course will lay the groundwork for social network analysis (SNA) from conceptual, statistical, empirical, and computational foundations. We will draw on the rich multidisciplinary history that has shaped the field's development - incorporating perspectives from sociology, physics, mathematics, statistics, and public health.

SNA differs from other analytic perspectives in ways that require unique strategies for data collection, storage, descriptive and statistical analyses. The course will address each of these strategies by surveying a range of the most commonly used analytic techniques. We will demonstrate their empirical applications and computation using the R programming language, and several other analysis and visualization packages, including UCINET, Pajek, and visone.

Topics to be discussed include a basic introduction to SNA, graphs and matrices, basic network measures and visualization, reciprocity and transitivity, dyadic and triadic analysis, centrality, egocentric networks, two-mode networks (affiliations, bibliographic/scientometric analysis), cohesive subgroups, equivalences and blockmodeling, hubs & authorities, cores & peripheries, clustering and graph partitioning, large scale structure of networks, statistical modeling in network (ergm/RSiena), and network dynamics and change in networks.

Software: We will use a number of packages: UCINET, Pajek, the statnet and other related packages in R, and visone.

Fees: Consult the fee structure.

Tags: network analysis, social structures, sociogram, dyadic analysis, graph theory, social network diagram, actor interrelations

Course Sections

Section 1

Location: ICPSR -- Ann Arbor, MI

Date(s): July 9 - July 20

Time: 3:00 PM - 7:00 PM


  • Ann McCranie, Indiana University