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On the topic of journalistic integrity, the current state of accurate,impartial news reporting has garnered much debate in context to the 2016 USPresidential Election. In pursuit of computational evaluation of news text, thestatements (attributions) ascribed by media outlets to sources provide a commoncategory of evidence on which to operate. In this paper, we develop an approachto compare partisan traits of news text attributions and apply it tocharacterize differences in statements ascribed to candidate, Hilary Clinton,and incumbent President, Donald Trump. In doing so, we present a model trainedon over 600 in-house annotated attributions to identify each candidate withaccuracy > 88%. Finally, we discuss insights from its performance for futureresearch.

Assessing Partisan Traits of News Text Attributions