#Polar Scores: Measuring partisanship using social media content. Issue 4 (1st October 2016)

• Record Type: Journal Article
• Authors: Hemphill, Libby; Culotta, Aron; Heston, Matthew
• Is Part Of: Journal of information technology & politics. Volume 13:Issue 4(2016)
• Page Start: 365
• Page End: 377
• Publication Date: 2016-10-01
• Subjects: Partisanship -- polarization -- political communication -- politicians -- social media -- Twitter; Electronic government information -- Periodicals; Internet in public administration -- Periodicals; Information technology -- Political aspects -- Periodicals; 320.0285
• DOI: 10.1080/19331681.2016.1214093
• Languages: English
• ISSNs: 1933-1681

Abstract

ABSTRACT: We present a new approach to measuring political polarization, including a novel algorithm and open source Python code, which leverages Twitter content to produce measures of polarization for both users and hashtags. #Polar scores provide advantages over existing measures because they (a) can be calculated throughout the legislative cycle, (b) allow for easy differentiation between users with similar scores, (c) are chamber-agnostic, and (d) are a generic approach that can be applied beyond the U.S. Congress. #Polar scores leverage available information such as party labels, word frequency, and hashtags to create an accessible, straightforward algorithm for estimating polarity using text.