Benefitting from the large-scale opportunities enabled by computational text analysis typically involves developing a central research question, designing an act of quantification related to that question, modifying existing data or collecting new data related to the question, and interpreting a principal measurement in a way that informs the initial research question. Research design describes the work of ensuring that the principal measurement will inform the initial question. This workshop will focus on strategies to make planning and implementing computational text analysis more manageable and increase the chances of an informative finding.

Instructor: Matthew Lavin, Clinical Assistant Professor of English and Director of Digital Media Lab