COMM 6750

Research Methods for Social Networks and Social Media

Course Description

Course information provided by the Courses of Study 2017-2018.

This course will train students to deploy network methods and computational techniques with the goal of using data to advance communication theory. Students will enter with a theoretical question that they believe can be tested with either social network data or data drawn from social media archives. They will learn relevant issues of research design, methods of data acquisition and appropriate methods of statistical analysis for data of this kind. Students will use this knowledge to produce a paper reporting the results of data analysis that addresses their question.

When Offered Fall.

Permission Note Enrollment limited to: graduate students.

• Students will gain the ability to evaluate social science research that uses social network methods. This will be achieved through reading and discussion of social scientific research papers with attention to a) whether variables have appropriately operationalized theoretical constructs, b) whether knowledge claims are justified by the data analysis presented.
• Students will improve their ability to do independent research using network analysis and social media data by producing a completed research paper using these methodologies.
• Students will learn to convert qualitative observations and theoretical hypothesis about social relationships and social interactions into quantifiable ideas which can be tested with communication network data or other behavioral data drawn from social media.
• Students will improve their speaking and writing skills, in particular in regard to articulating theoretical ideas about collective social behavior - conversations, the evolution of groups, the diffusion of ideas -- in quantifiable ideas that can be tested with data. Students will be engaged actively in oral discussions in class. The final paper will be of quality appropriate to submit to a conference.
• Students will work on "lab" assignments. Some lab assignments will be collaborative and require students with diverse skills (e.g. those with a strong theory background can work with those with strong data extraction and analysis skills) to work together.

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