CONSTRUCTING RELATIONAL AND VERIFIABLE PROTEST EVENT DATA: FOUR CHALLENGES AND SOME SOLUTIONS*
We call for a relational approach to constructing protest event data from news sources to provide tools for detecting and correcting errors and for capturing the relations among events and between events and the texts describing them. We address two problems with most protest event datasets: (1) inconsistencies and errors in identifying events and (2) disconnect between data structures and what is known about how protests and media accounts of protests are produced. Relational data structures can capture the theoretically important structuring of events into campaigns and episodes and media attention cascades and cycles. Relational data structures support richer theorizing about the interplay of protests and their representations in news media discourses. We present preliminary illustrative data about Black protests from these new procedures to demonstrate the value of this approach.
Contributor Notes
† This research was funded by National Science Foundation grants SES1423784 and SES 1918342. The authors thank Morgan C. Matthews, David Skalinder, and John Lemke for research assistance and conversations that contributed to the development of our methods. Our research protocols and recommendations have developed substantially across the course of this work through several conference presentations and working papers posted to SocArXiv since 2017. The online appendix and replication data are posted at https://osf.io/mp8gs/.