More Voices Than Ever? Quantifying Media Bias in Networks

TL;DR

This paper introduces empirical measures to quantify and compare media bias in social media (blogs) and mainstream news, focusing on coverage quantity related to US Congress stories, revealing distinct bias characteristics and coverage processes.

Contribution

It develops a systematic, data-driven approach to measure and compare media bias in social and mainstream media, highlighting differences in coverage dynamics.

Findings

Blogs and news media exhibit different bias patterns.

Coverage selection processes differ between social and mainstream media.

Empirical measures effectively quantify media bias.

Abstract

Social media, such as blogs, are often seen as democratic entities that allow more voices to be heard than the conventional mass or elite media. Some also feel that social media exhibits a balancing force against the arguably slanted elite media. A systematic comparison between social and mainstream media is necessary but challenging due to the scale and dynamic nature of modern communication. Here we propose empirical measures to quantify the extent and dynamics of social (blog) and mainstream (news) media bias. We focus on a particular form of bias---coverage quantity---as applied to stories about the 111th US Congress. We compare observed coverage of Members of Congress against a null model of unbiased coverage, testing for biases with respect to political party, popular front runners, regions of the country, and more. Our measures suggest distinct characteristics in news and blog media. A simple generative model, in agreement with data, reveals differences in the process of coverage selection between the two media.