  We perform an automatic analysis of television news programs, based on the
closed captions that accompany them. Specifically, we collect all the news
broadcasted in over 140 television channels in the US during a period of six
months. We start by segmenting, processing, and annotating the closed captions
automatically. Next, we focus on the analysis of their linguistic style and on
mentions of people using NLP methods. We present a series of key insights about
news providers, people in the news, and we discuss the biases that can be
uncovered by automatic means. These insights are contrasted by looking at the
data from multiple points of view, including qualitative assessment.
