量化Twitter上的两极分化:卡瓦诺的提名（Social and Information Networks）
- 2020 年 1 月 9 日
- 筆記
这篇论文讨论了两级分化的量化，特别是关于布雷特·卡瓦诺(Brett Kavanaugh)在美国最高法院的提名，以及他随后以1881年以来最微弱的优势获得最终肯定。共和党(GOP)和民主党(DNC)参议员以压倒性多数投票支持党派路线。在这篇文章中，我们研究了关于Twitter用户提名的政治两级分化。为了做到这一点，我们使用半监督和监督分类准确地识别了超过12.8万名Twitter用户对卡瓦诺提名的立场。接下来，我们量化了不同群体之间的两极分化，包括他们转发了谁，以及他们使用了哪些标签。我们修改了现有的量化措施，使其更有效。我们也描述了支持和反对提名的用户之间的两极分化。
原文题目：Social and Information Networks: Quantifying Polarization on Twitter: the Kavanaugh Nomination
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.
原文作者：Kareem Darwish
原文链接：https://arxiv.org/abs/2001.02125
