Intermediate SNA UCINET

Overview

This course is taught by Steve Borgatti. It  is a more technical and in-depth workshop than the Introductory workshop, but covers many of the same concepts. It focuses on the concepts and methods of SNA, particularly as they apply to specific research objectives. In this course, everything is related back to the research questions -- how the network analysis relates to consequences of interest.  In addition, the mathematics and algorithms behind the measures and techniques are explained. Prior familiarity with network analysis and research in general is assumed. 

This workshop uses the UCINET software  package extensively.  Important note: UCINET is Windows-only software. Please visit our software page in advance of the workshop.  

The course meets for five consecutive days starting June 5: Monday - Friday from 10:00-12:00 ET and 12:45-2:45 ET. There is a 45min lunch break at 12.  In addition, the instructor will normally be available after class for questions. TAs (scroll down for contact info) will be available during the sessions to catch people up, answer questions, and bring questions to the instructor's attention.  The 5th day of the workshop will be led by the TAs.

Logistics

Zoom info will be emailed to participants a few days before the workshop. In addition, you will be given access to a portal containing links to slides, videos, exercises, handouts, etc. Note that when doing a hands-on software-intensive workshop via Zoom, it is helpful to have two screens -- one to watch what the instructor is doing, and one to show what you are typing on your own machine. 

Schedule

1 Monday - Intro

• Overview of network analysis: the network perspective

• Working with network data in UCINET

• Visualizing network data

2 Tuesday – Node-level measures

• Characterizing a node's immediate environment

• Structural holes

• Centrality

3 Wednesday – Statistical models

• MR-QAP & LR-QAP

• Brief introduction to ERGM & related models

4 Thursday – Groups

• Group-level measures

• Community detection

TA contact information

• Diane Kang <DianeKang@uky.edu>

Recommended Readings

• Borgatti, SP, Everett, MG & Johnson, JC. 2018.  Analyzing Social Networks. 2nd Edition. London: Sage. 

  1.  Although we won't be using R in the workshop, you might be interested in our new book, Analyzing Social Networks Using R (2022).

• Borgatti, SP and Everett, MG. 2021? “Three Perspectives on Centrality.” In The Oxford Handbook of Social Networks, edited by James Moody. Oxford University Press [pdf]

Special Data

• In case some people have issues with using the "data for learning ucinet.xlsx" file, some key datasets in ucinet format can be found here