This is an open-source textbook that covers the basic approaches to the analysis of social network data. It also shows how approaches are implemented in the methodologies that many social network analysts use. This open textbook details how to conduct and present research on social networks. It includes theoretical information including how to use statistics in this research. It also includes detailed information on how to use the UCINET software.
To help students understand what social network analysis involves. To show students that social network analysis is a continuously and rapidly evolving field, and is one branch of the broader study of networks and complex systems. This is a reference site for researching social networks.
Target Student Population:
The book is most suitable as course-support for undergraduate or introductory graduate training in social network analysis. Undergraduate or graduate courses in the social sciences, including marketing, sociology, political science, or psychology.
Prerequisite Knowledge or Skills:
While this text is not a user's guide to UCINET (a social network analysis software package), it may be of assistance to beginning users.
Type of Material:
Open source textbook.
This could be used as the sole textbook for a social network analysis course or as supplemental readings on a social networking module within a larger course.
Evaluation and Observation
The text covers eighteen different topics associated with social network analysis. The information covers both theoretical and practical applications of social network analysis. Below are the 18 topics:
1. Social network data
2. Why formal methods?
3. Using graphs to represent social relations
4. Working with Netdraw to visualize graphs
5. Using matrices to represent social relations
6. Working with network data
9. Ego networks
10. Centrality and power
11. Cliques and sub-groups
12. Positions and roles: The idea of equivalence
13. Measures of similarity and structural equivalence
14. Automorphic equivalence
15. Regular equivalence
16. Multiplex networks
17. Two-mode networks
18. Some statistical tools
The site is very comprehensive and informed by scholarly work.
The chapters end with review and application questions, but an instructor would still need to provide context and perhaps an assignment. The information covered in this book may be too advanced for some types of students. It really depends on what type of student and what course this information is used.
Potential Effectiveness as a Teaching Tool
The chapters are well-written and the concepts build progressively. The potential effectiveness is the biggest strength of this module. Assuming that this open source textbook is used in an appropriate course, it is an outstanding reference on social network research and information. The material is presented in a sequential and logical manner.
The instructor would need to set the context of the material depending on the discipline within the social sciences.
Ease of Use for Both Students and Faculty
The module is very easy to navigate, well-written, and very simple. Each chapter contains a "sub-menu" at the top of each page to help users find the sub-sections within each chapter. The pages are not cluttered with ads, graphics, or other material that may distract the student. The site is exceptionally easy to use and has some good graphs and matrices to illustrate the material.
The site is very basic and resembles websites of the late 1990s (e.g., chapters that are one long page and begin with section links). Some students may find the interface to be too boring and plain. But they should not experience any problems finding the material.
Other Issues and Comments:
I'm not sure that this module should be categorized in marketing. It seems more appropriate for a different discipline. The social networking dimension is marketing-oriented, but this module is probably a bit too technical to be just marketing.