Shedding (a Thousand Points of) Light on Biased Language

Abstract

This paper considers the linguistic indicators of bias in political text. We used Amazon Mechanical Turk judgments about sentences from American political blogs, asking annotators to indicate whether a sentence showed bias, and if so, in which political direction and through which word tokens. We also asked annotators questions about their own political views. We conducted a preliminary analysis of the data, exploring how different groups perceive bias in different blogs, and showing some lexical indicators strongly associated with perceived bias.