Politics and political conflict often occur in the written and spoken word. Scholars have long
recognized this, but the massive costs of analyzing even moderately sized collections of …

A guide for using computational text analysis to learn about the social world From social
media posts and text messages to digital government documents and archives, researchers …

Existing approaches to measuring political disagreement from text data perform poorly
except when applied to narrowly selected texts discussing the same issues and written in …

This article develops a generalized supervised learning methodology for inferring roll‐call
scores from campaign contribution data. Rather than use unsupervised methods to recover …

政策文本计算:一种新的政策文本解读方式* Page 1 2016 年第6 期 编者按:当Jim Gray 提出数据
密集型科学研究范式,David Lazer 提出计算性社会科学等研究理念后,以数据分 析和计算思维为 …

Inter-personal affiliations and coalitions are an important part of politicians' behaviour, but
are often difficult to observe. Since an increasing amount of political communication now …

Assigning political actors positions in ideological space is a task of key importance to
political scientists. In this paper we compare estimates obtained using the automated …

Wordscores is a popular computational text analysis method with numerous applications in
communication research. Wordscores claims to scale documents on specified dimensions …

Social scientists have long studied international differences in political culture and
communication. An influential strand of theory within political science argues that different …

Probabilistic methods for classifying text form a rich tradition in machine learning and natural
language processing. For many important problems, however, class prediction is …