The past decade has seen a renaissance in the development of political event data sets.
This has been due to at least three sets of factors. First, there have been technological …

Despite the popularity of unsupervised techniques for political science text-as-data research,
the importance and implications of preprocessing decisions in this domain have received …

Understanding the causes of interstate conflict continues to be a primary goal of the field of
international relations. To that end, scholars continue to rely on large datasets of conflict in …

Support Vector Machines (SVMs) are classic supervised learning models for classification,
regression and distribution estimation. A survey conducted by Kaggle in 2017 shows that …

Learning paths are curated sequences of resources organized in a way that a learner has all
the prerequisite knowledge needed to achieve their learning goals. In this article, we …

This article introduces the latest iteration of the most widely used dataset on interstate
conflicts, the Militarized Interstate Dispute (MID) 5 dataset. We begin by outlining the data …

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 …

A hands on guide to web scraping and text mining for both beginners and experienced
users of R Introduces fundamental concepts of the main architecture of the web and …

The (unheralded) first step in many applications of automated text analysis involves
selecting keywords to choose documents from a large text corpus for further study. Although …

Established approaches to analyze multilingual text corpora require either a duplication of
analysts' efforts or high-quality machine translation (MT). In this paper, I argue that …