Using Machine Learning Techniques to Understand Crisis Framing in Immigration Coverage by American Newspapers, 1980-2021

Featured speakers: Shawn Walker and Allan Colbern

In this talk, join the ASU Library's Data Science and Analytics unit as we discuss the complexities and complications of using machine learning techniques like topic modeling, Named Entity Recognition (NER), and corpus linguistics to assist in the qualitative coding and exploration of a large new dataset. In the project we explored an original dataset composed of four national and seven state-based newspapers, and one Canadian newspaper, from 1980 to 2021, which vary as conservative or as progressive sources (resulting in a corpus of 106,000 total news articles).