Visualizing textual models with in-text and word-as-pixel highlighting

06/20/2016
by   Abram Handler, et al.
0

We explore two techniques which use color to make sense of statistical text models. One method uses in-text annotations to illustrate a model's view of particular tokens in particular documents. Another uses a high-level, "words-as-pixels" graphic to display an entire corpus. Together, these methods offer both zoomed-in and zoomed-out perspectives into a model's understanding of text. We show how these interconnected methods help diagnose a classifier's poor performance on Twitter slang, and make sense of a topic model on historical political texts.

READ FULL TEXT

Please sign up or login with your details

Forgot password? Click here to reset