The Use of Newspaper Data in the Study of Collective Action

TLDR

Collective action research increasingly relies on newspaper accounts of protest events, a practice that has grown over the past decade and is accompanied by a critical literature focusing on selection and description bias, including coverage decisions influenced by event type, news agency, and issue. This review aims to discuss methods for detecting bias in protest event data and how to incorporate such bias knowledge into data interpretation. The authors review analytical strategies for identifying bias and integrating bias awareness into the interpretation of protest event datasets. When reported, the hard news coverage of protest events is generally accurate.

Abstract

Studying collective action with newspaper accounts of protest events, rare only 20 years ago, has become commonplace in the past decade. A critical literature has accompanied the growth of protest event analysis. The literature has focused on selection bias—particularly which subset of events are covered—and description bias—notably, the veracity of the coverage. The “hard news” of the event, if it is reported, tends to be relatively accurate. However, a newspaper's decision to cover an event at all is influenced by the type of event, the news agency, and the issue involved. In this review, we discuss approaches to detecting bias, as well as ways to factor knowledge about bias into interpretations of protest event data.