Political Polarization and Media in a Multi-Party System: A Case Study of Turkey

Abstract

Political media bias is an important problem in political communications literature. In this article, extending on the selective exposure theory by publicly available social media data, I first propose an audience similarity metric for news organizations. Then by adopting a network theoretical approach I provide a computational framework for inferring media groups at different granularities. Furthermore, a novel method for calculating media-party parallelism (MPP) using social media is introduced. To evaluate the robustness of the methods better, a country whose media system is known to have a high degree of polarized pluralism and political parallelism is chosen as a test case. For that matter, two kinds of observational datasets of Turkey is compiled using Twitter API: the first being the news audience dataset and the second one relating to the political audience. In particular, by collecting data before and after two major developments in Turkish politics, their effects to the media system are investigated. First, algorithmically identified media clusters at different scales help explain the diversity in researchers’ categorizations of the Turkish media organizations. Second, through MPP analysis I show that outlet preferences of Turkish parties are quite different from one another, and identified an inverse correlation between the ruling party and the main opposition party. Findings regarding MPP are not only verified by comparing the measurements before and after the major developments as a longitudinal study, but also validated by the results of cross-sectional surveys. Finally, interactive visualizations are created to facilitate the interpretation of the results and to highlight the findings.