Teacher Language Use Around Critical Race Theory (CRT) and Anti-CRT Laws: A Machine Learning Text Analysis

• In Event: Toward Racial Justice in Education Policy: From Interrogating Thoughts and Actions to Organizing and Allyship

Abstract

This paper uses machine learning text analysis techniques to investigate content, sentiment, and frequency of posts relating to Critical Race Theory (CRT) and anti-CRT laws in online social media United States (U.S.) teacher spaces by political ideology. Overall, Left teacher spaces discuss CRT the most, while Right and Non-partisan teacher spaces discuss this subject very little, implying that other topics are of greater importance to them. All teacher spaces were relatively positive in terms of their sentiment, with Non-partisan teacher posts being the most positive. Lastly, there were some increases in teachers’ discussion of CRT-related terms after the proposal and passing of these laws, though unigram analysis showed more of their use before January 2021.

Author

• Claire E. Delcourt, Teachers College, Columbia University