Constructing Relational and Verifiable Protest Event Data
Four Challenges and Some Solutions
Bibliographic Data
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
Data mining · Data science · Event (particle physics · Event data · Political science · Relational database · Structuring · Verifiable secret sharing · Community Health and Development · Computer Science · Political Conflict and Governance · Qualitative Comparative Analysis Research
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Breaking the mold
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Papea
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| Citations per year | 4.5 |
|---|---|
| Citation span | 2024 - 2026 (3) |
| Highly cited | No |