作者
Libby Hemphill, Aron Culotta, Matthew Heston
发表日期
2016/10/1
期刊
Journal of Information Technology & Politics
卷号
13
期号
4
页码范围
365-377
出版商
Routledge
简介
We present a new approach to measuring political polarization, including a novel algorithm and open source Python code, which leverages Twitter content to produce measures of polarization for both users and hashtags. #Polar scores provide advantages over existing measures because they (a) can be calculated throughout the legislative cycle, (b) allow for easy differentiation between users with similar scores, (c) are chamber-agnostic, and (d) are a generic approach that can be applied beyond the U.S. Congress. #Polar scores leverage available information such as party labels, word frequency, and hashtags to create an accessible, straightforward algorithm for estimating polarity using text.
学术搜索中的文章
L Hemphill, A Culotta, M Heston - Journal of Information Technology & Politics, 2016