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Quantifying Polarization on Twitter: The Kavanaugh Nomination

  • Kareem DarwishEmail author
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 11864)

Abstract

This paper addresses polarization quantification, particularly as it pertains to the nomination of Brett Kavanaugh to the US Supreme Court and his subsequent confirmation with the narrowest margin since 1881. Republican (GOP) and Democratic (DNC) senators voted overwhelmingly along party lines. In this paper, we examine political polarization concerning the nomination among Twitter users. To do so, we accurately identify the stance of more than 128 thousand Twitter users towards Kavanaugh’s nomination using both semi-supervised and supervised classification. Next, we quantify the polarization between the different groups in terms of who they retweet and which hashtags they use. We modify existing polarization quantification measures to make them more efficient and more effective. We also characterize the polarization between users who supported and opposed the nomination.

Keywords

Political polarization Polarization quantification Stance detection 

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Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  1. 1.Qatar Computing Research Institute, HBKUDohaQatar

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