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Georgetown University


Detailed Course Information


Fall 2017
Sep 28, 2022
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Information Select the desired Level or Schedule Type to find available classes for the course.

CCTP 696 - Social Network Analysis
Course Title: Social Network Analysis
*Fulfills CCT Core Methods Requirement

Social Network Analysis (SNA) allows patterns in relationships to be graphed and explored. Whether tracking the flow of information or influence, Social Network Analysis provides a valuable tool for uncovering important insights that other methods of analysis may miss. 

This class balances theory and practice, concepts and computations, with the goal of enabling students to conduct SNA research of their own. Students will learn how SNA is currently being used—applications that include analysis of political data, studying terrorism and tracking disease spread, among others. Students will also learn how to graph relationships given a set of data and the math techniques that unearth key pieces of information in these graphs. 

Data collection methods will be explored. Strategies for efficient coding and data entry are key aspects of the course that aim to build practical skills. Bimodal networks are also a major topic with particular focus on applications to support collaboration in the workplace. Methods to extract hyperlink networks quickly will be introduced along with methods to explore URL diffusion via social media The primary textbook Networks, Crowds and Markets also facilitates close attention to information cascades and the diffusion of innovation. 

Students will learn relevant mathematical techniques in a supportive, highly verbal manner. Students will also learn computer based SNA techniques using both Excel and NodeXL software. Students will gain matrix manipulation skills and data management skills with Excel. These will assist students in completing research projects during the last five weeks of the class.

No particular math background is required beyond a willingness to learn. This course fulfills the CCT Core Methods requirement.

3.000 Credit hours
3.000 Lecture hours
0.000 Lab hours

Levels: MN or MC Graduate, Undergraduate
Schedule Types: Lecture, Seminar

Commun, Culture & Technology Department

Must be enrolled in one of the following Levels:     
      MN or MC Graduate
Must be enrolled in one of the following Majors:     
      Commun, Culture & Technology

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