SOC 6410

SOC 6410

Course information provided by the Courses of Study 2014-2015.

It will introduce graduate students to the methodology of social network analysis. We will begin by discussing the different types of network data before exploring how these data are collected, and the strengths and limitations of each resulting data structure. We will then learn about methods of data cleaning and the particular complications that non-response or truncated responses can introduce to network studies. Finally, we will introduce several types of analytic approaches including ego-network data analysis, MRQAP, Stochastic Actor-Oriented Models (Siena), and Exponential Random Graph models (ERGMs). Familiarity with R will be helpful but is not required. Students will be expected to develop their own network project throughout the semester, potentially collecting their own data.

When Offered Fall.

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Syllabi: none
  •   Regular Academic Session. 

  • 4 Credits Grade(GRV)

  • 17111 SOC 6410   SEM 101

  • Instruction Mode: