量化Twitter上的兩極分化:卡瓦諾的提名（Social and Information Networks）
- 2020 年 1 月 9 日
- 筆記
這篇論文討論了兩級分化的量化，特別是關於布雷特·卡瓦諾(Brett Kavanaugh)在美國最高法院的提名，以及他隨後以1881年以來最微弱的優勢獲得最終肯定。共和黨(GOP)和民主黨(DNC)參議員以壓倒性多數投票支援黨派路線。在這篇文章中，我們研究了關於Twitter用戶提名的政治兩級分化。為了做到這一點，我們使用半監督和監督分類準確地識別了超過12.8萬名Twitter用戶對卡瓦諾提名的立場。接下來，我們量化了不同群體之間的兩極分化，包括他們轉發了誰，以及他們使用了哪些標籤。我們修改了現有的量化措施，使其更有效。我們也描述了支援和反對提名的用戶之間的兩極分化。
原文題目：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
原文鏈接：https://arxiv.org/abs/2001.02125
