This Fall, John Mohr and I ran a pilot program for teaching Sociology undergraduates how to use topic modeling in their projects. The pilot program lasted only about 4 weeks and students were asked to prepare a text corpus of approximately 100 documents using LexisNexis (or copy-paste from the web) and perform analysis using Excel or Google Sheets. Past mentoring projects of both John and I showed that undergraduates can come up with some pretty creative ways to use these computational analysis tools, even if they can’t write the code to do it themselves (see my summer mentorship project). Beyond the technical, the most challenging part of this work is getting students to think about what information they can get from large corpora and how to use the tools to answer questions of interest. It is clear that the era of Big Data and access to internet has changed the way social processes occur on a large scale (think Fake News), so we need to train social scientists to use new tools and think about data differently.
This summer I had the opportunity to work with sociology undergraduate student Emma Kerr as part of her summer research internship with the UCSB IGERT program. Emma proposed a project investigating whether or not news coverage of Betsy DeVos was more focused on her personal life or her policy initiatives relative to other SoE. The summer program is designed to introduce big data and network science to students with interdisciplinary backgrounds. Emma had taken a computational sociology class at UCSB with John Mohr working on Twitter analysis and really enjoyed it, so I thought she would be a good fit for the program.