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Application of Sentiment and Topic Analysis to Teacher Evaluation Policy in the U.S

We examine the potential value of Internet text to understand education policy related to teacher evaluation. We discuss the use of sentiment analysis and topic modeling using articles from the New York Times and Time Magazine, to explore media portrayal of these policies. Findings indicate that sentiment analysis and topic modeling are promising methods for analyzing Internet data in ways that can inform policy decision-making, but there are limitations to account for when interpreting patterns over time.