This is a PhD level course on social network analysis. The focus is both theoretical (e.g., what are the key concept of social network analysis) and methodological (e.g., how do we actually carry out research on social networks). What the course is not is a survey of social network research to date (we have a separate course for that taught by Prof. Dan Brass). The course begins with a definition of a social network and a review of key concepts from the underlying mathematical field of graph theory. We then move on to dyadic concepts in network analysis, such as the notion of graph-theoretic distance. Next we cover node-level concepts, such as centrality and ego-network structure. Next we cover whole-network level concepts, such as network density. The end of the course is devoted to issues of research design and methodology, including data collection and analysis techniques.
GOALS AND OUTCOMES
This is a hands-on course with the objective of teaching a student how to do a network analysis. At the end of this course, a student should be able design and implement a social network analysis research project, including analyzing the data and writing up the results for a journal.
The deliverables for this course include:
- Weekly homework assignments demonstrating mastery of analysis techniques
- A publishable research paper
In addition, the Dept. of Management students enrolled in the course are required to make a presentation on the results of their research project. All other students are invited to give a presentation as well, but this is optional.
Analyzing Social Networks by Borgatti, Everett and Johnson (2013). It is available online at Amazon or Sage. In the schedule, this book is referred to as ASN.
In addition, I recommend purchasing Wasserman and Faust's (1994) Social Network Analysis. Although a bit dated, it is still a very useful reference book.
Another book I recommend is the Sage Handbook of Social Network Analysis edited by Scott and Carrington (2012).
In addition, we will be using the UCINET software. You should download and install UCINET as soon as possible in order to iron out any problems. A free registration code will be made available to you in class (but the program will run for 60 days without the registration code).
CONTENT OUTLINE AND SCHEDULE
CONTENT OUTLINE AND SCHEDULE
The topics and assignments for each week are given in the schedule of classes, which can be found at this url:
ASSIGNMENTS AND GRADING
Grading for this course is based on just two things: (1) a research paper (worth 75% of your grade), and (2) class participation (worth 25%). There are no exams in this course.
Research Paper (75%). For the paper, you must design and implement an empirical study of social networks. While you are not required to submit this paper to a journal for publication, it should be of publishable quality and written up in Academy of Management Journal format. Copies of past (successful) papers are available on the class website. The paper is due via email exactly one week after the last class (see the schedule for the exact date).
Class Participation (25%). I expect active participation in the classroom. My hope is that you will want to participate because we will be discussing interesting ideas. The abilities to interact with your colleagues effectively, to contribute to a group discussion, and to advocate an informed position are essential skills that will prepare you for the transition to a professional career. Your participation grade is based on your preparedness for class (e.g., having read the assigned reading), demonstration of a firm grasp of material covered, a willingness to seek clarification as appropriate, and the ability to integrate concepts and multiple perspectives. I will grade your participation according to the following criteria:
- - the frequency and quality of your contributions to classroom activities
- - the frequency and quality of your answers to the case discussion questions
- - the quality of your feedback to presentations of other students
- - the assessment provided by your fellow team members of your contribution to team assignments and discussions
The correspondence between letter grades and numerical percentages is as follows:
90 – 100%
80 – 89%
70 – 79%
0 – 69%
As a PhD course, attendance is not strictly required, but it is expected (and necessary for a good participation grade). I would appreciate being notified ahead of time if you are not going to be attending any particular class.
You have a responsibility to maintain the highest standards of academic integrity in both individual and group work, and to comply with the University of Kentucky policy on academic integrity. Any instances of cheating or plagiarism will be subject to the disciplinary procedures of the University. Please speak to me if you have any questions about academic integrity or concerns about any classmate’s behavior. Please bring any ethical questions or concerns to me before submitting an assignment or participating in an activity (such as in-class exams and activities). Two general rules of thumb: When in doubt about using material, make sure you cite it. When in doubt about collaborating, sharing, etc., don’t do it without checking with me.
If you have a documented disability that requires academic accommodations, please see me as soon as possible during scheduled office hours. In order to receive accommodations in this course, you must provide me with a Letter of Accommodation from the Disability Resource Center (Room 2, Alumni Gym, 257‐2754, email address email@example.com) for coordination of campus disability services available to students with disabilities.
The preferred way to contact me is via email (firstname.lastname@example.org). You can also try my office phone (257-2257) or just drop by my office (B&E 455Y). Office hours are by appointment only, which you can arrange by email