The increasing trend of political polarization in the U.S. is reflected in media consumption patterns that indicate partisan polarization.

The primary objective of this paper was to develop a model capable of characterizing the biases of cable news programs given a large volume of text data

This research yielded several significant results. Firstly, our findings suggest that it is feasible to computationally extract media bias characterizations

The program clusters are consistent over time, although there are a few periods of major movement between months.