The preconference will take place Friday, October 4, from 1:30-5:00 pm.
Computational Methods in Organizational Communication Research
In recent years a “third way” for methodology has developed in organizational communication research focusing on computational methods. These methods are useful for both qualitatively- and quantitatively-oriented scholars and enable them to answer questions traditional methods cannot easily address. This workshop will focus on two methods: machine learning and text analytics.
A social science introduction to machine learning
Dr. Andy Pilny, University of Kentucky
Machine learning (ML) algorithms have the ability to handle large amounts of cases and variables, which make them increasingly useful in the age of Big Data. This workshop is a gentle and applied introduction on how to implement ML for social science research, paying particular attention to organizational communication. Five key issues will be presented: (1) Variable preparation, (2) variable selection, (3) model selection, (4) model evaluation, and (5) model validity. Participants are welcome to follow along and participate on their own computers in the interactive demo.
Resources:
An introduction to computational text analysis
Jeff Proulx, University of Illinois at Urbana-Champaign
Computational text analysis allows scholars to process, explore, and model large corpora of text. Natural language processing techniques such as topic modeling are increasingly important tools for communication researchers. This workshop is an applied introduction to computational text analysis with a specific focus on topic modeling in organizational communication. The workshop will primarily focus on four key issues: (1) Identifying use cases, (2) data preparation, (3) model evaluation, and (4) model interpretation. Participants are welcome to follow along and participate on their own computers in the interactive demo.
R: https://ftp.ussg.iu.edu/CRAN/
R Studio: https://rstudio.com/products/rstudio/download/#download
Workshop Materials: https://uofi.box.com/s/37840r6s7mwk58vcwoug3yx6jysaj5bk