Searching and Clustering Methodologies: Connecting Political Communication Content across Platforms. Issue 1 (May 2015)

• Record Type: Journal Article
• Authors: Driscoll, Kevin; Thorson, Kjerstin
• Editors: Shah, Dhavan V.; Cappella, Joseph N.; Neuman, W. Russell
• Is Part Of: Annals of the American Academy of Political and Social Science. Volume 659:Issue 1(2015:May)
• Page Start: 134
• Page End: 148
• Publication Date: 2015-05
• Subjects: political communication -- social media -- content analysis -- cluster analysis -- text mining; Social sciences -- Periodicals; Social sciences -- United States -- Periodicals; Political science -- Periodicals; United States -- Politics and government -- Periodicals; 300
• DOI: 10.1177/0002716215570570
• Languages: English
• ISSNs: 0002-7162

Abstract

People create, consume, and share content online in increasingly complex ways, often including multiple news, entertainment, and social media platforms. This article explores methods for tracing political media content across overlapping communication infrastructures. Using the 2011 Occupy Movement protests and 2013 consumer boycotts as cases, we illustrate methods for creating integrated datasets of political event-related social media content by (1) using fixed URLs to link posts across platforms ( URL-based integration) and (2) using semiautomated text clustering to identify similar posts across social networking services ( thematic integration). These approaches help to reveal biases in the way that we characterize political communication practices that may occur when we focus on a single platform in isolation.