Kimberly Fredericks, Ph.D. Dean, The School of Management; The Sage Colleges
This eStudy is geared for an audience that is at the novice level of experience and expertise in social network analysis. Interest in the field of social network analysis has grown considerably over the last decade. Social network analysis takes seriously the proposition that the relationships between individual units or actors are non-random and that their patterns have meaning and significance. It seeks to operationalize concepts such as position, role, or social distance that are sometimes used casually or metaphorically in social, political, and/or organizational studies. This eStudy course seeks to provide an introduction to social network analysis theories, concepts, and applications within the context of evaluation. Participants will be come to a basic understanding of network concepts, methods, and the software that provides for analysis of network properties. Participants will be exposed to real world examples and discussion to facilitate a better understanding of network structure, function and data collection.
Attendees will understand the theories and concepts around SNA.
Attendees will learn the parameters around what research questions are best suited for the use of SNA.
Attendees will learn how to match research questions and data collection methods within a larger evaluation context.
Attendees will understand basic SNA survey construction.
Attendees will see how to enter and manipulate data in UCINET and Netdraw.
Attendees will see to produce basic output and analyze their findings within UCINET and Netdraw.
Kimberly Fredericks frequently conducts social network analysis for both AEA and the Evaluators Institute. Kim is a regular author and speaker on this subject, including co-editing an issue of New Directions in Evaluation on Social Network Analysis in Program Evaluation.
Evaluators and program officers looking to better understand SNA as a methodology and when it is best utilized in their work is the primary audience for this workshop. Attendees should have some basic knowledge of research methodology, but need not have in-depth knowledge or skills particular to SNA.