论文标题
在Twitter上量化两极分化：Kavanaugh提名
Quantifying Polarization on Twitter: the Kavanaugh Nomination
论文作者
论文摘要
本文介绍了两极分化的量化，特别是与提名布雷特·卡瓦诺（Brett Kavanaugh）提名美国最高法院的提名，以及他随后的确认，并以1881年以来最狭窄的利润。共和党人（GOP）和民主党（DNC）参议员沿党派压倒性地投票。在本文中，我们研究了有关Twitter用户提名的政治两极分化。为此，我们准确地使用半监督和监督分类来准确地确定了超过12.8万个Twitter用户对Kavanaugh提名的立场。接下来，我们会根据转发和使用哪些主题标签来量化不同组之间的两极分化。我们修改现有的极化定量指标，以使其更有效，更有效。我们还表征了支持和反对提名的用户之间的两极分化。
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.
