From Fishing Poles to Digital Dragnets: Searching for Pirates with New Tools

Sunday, January 11, 2026: 9:00 AM
Monroe Room (Palmer House Hilton)
James Rankine, Rochester Institute of Technology
Piracy has always contained a frustrating tension for historians. The phenomenon of maritime predation is undeniably an attractive subject: dramatic, profoundly disruptive, often marginal, and intensively scrutinised, pirates offer scholars insights rarely found elsewhere. The same qualities that make pirates attractive, however, also render them an elusive quarry for the researcher due to fragmentary and sometimes contradictory evidence in historical records. While recent work has made tremendous strides in confronting the historiographic and methodological difficulties this presents, quantitative analyses of piracy’s extent, intensity, and geography remain as elusive as ever. Estimates of how many pirate vessels–to say nothing of how many pirates– were active and where vary considerably, and so do the assessments they underpin. A digital historical approach, focused on quantitative methods may seem antithetical to the patchy, contested, and vague historical portrait of piracy.

This paper argues that when approached with the insights of recent scholars, and by carefully avoiding the positivist leanings of quantitative analysis, collecting and databasing evidence about pirates offers not only a clearer and more strongly evidence portrait of pirates and their activities, but also new insights and opportunities for scholarship in the field. The Pirate History Database comprises thousands of contemporary Anglophone newspaper reports of pirate activities across the Atlantic between 1680 and 1760, with a particular focus on the early eighteenth century ‘Golden Age’. This database is by no means definitive, nor is it a solution to piracy’s epistemological tensions. However, through an exploration of the what it has already revealed, I contend that the database can serve as both a model and as a foundation for a broader, more inclusive, disciplined and interdisciplinary approach to developing more reliable, comprehensive, and granular data about a phenomenon long subjected to incomplete and impressionistic assessments of its size, scope, and meaning.

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