Data-driven and machine learning based approaches for detecting, categorising and
measuring abusive content such as hate speech and harassment have gained traction due …

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 …

In a recent article, Gibler, Miller, and Little (2016)(GML) conduct an extensive review of the
Militarized Interstate Dispute (MID) data between the years 1816 and 2001, highlighting …

The adage “All politics is local” in the United States is largely true. Of the United States'
90,106 governments, 99.9% are local governments. Despite variations in institutional …

Crowdsourcing opens the door to solving a wide variety of problems that previously were
unfeasible in the field of machine learning, allowing us to obtain relatively low cost labeled …

Open-ended questions in surveys are often manually coded into one of several classes (or
categories). When the data are too large to manually code all texts, a statistical (or machine) …

The majority of studies on international conflict escalation use a variety of measures of
hostility including the use of force, reciprocity, and the number of fatalities. The use of …

The Border Crossings of the World (BCW) dataset explores state authority spatially by
collecting information about infrastructure built where highways cross internationally …

The great promise of social media platforms such as Twitter is to connect people separated
across time and space. This has had far-ranging consequences for politics by changing …

Responses to open-ended questions in surveys are usually coded into pre-specified
classes, manually or automatically using a statistical learning algorithm. Automatic coding of …