量化Twitter上的两极分化：卡瓦诺提名
Quantifying Polarization on Twitter: the Kavanaugh Nomination
摘要：
本文讨论了极化量化，特别是因为它涉及到布雷特卡瓦诺的提名，美国最高法院和他随后的确认自1881年以来的最高保证金。共和党（GOP）和民主党（DNC）参议员以压倒性优势投票。在本文中，我们研究政治两极分化的Twitter用户之间的提名。为此，我们使用半监督和监督分类准确识别了超过12.8万Twitter用户对卡瓦诺提名的立场。接下来，我们根据他们转发的人和他们使用的标签来量化不同群体之间的两极分化。我们修改现有的极化量化措施，使他们更有效率和更有效的。我们还描述了支持和反对提名的用户之间的两极分化。
英文摘要：
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.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
