CLFeb 4, 2020

Plague Dot Text: Text mining and annotation of outbreak reports of the Third Plague Pandemic (1894-1952)

arXiv:2002.01415v35 citations
AI Analysis

This work addresses the challenge for historians and epidemiologists in extracting insights from narrative-based outbreak data, though it is incremental as it builds on existing text mining and OCR methods.

The researchers tackled the problem of analyzing unstructured historical outbreak reports by creating a structured corpus from over 100 reports of the Third Plague Pandemic using text mining and manual annotation, enabling search and analysis for future epidemiological research.

The design of models that govern diseases in population is commonly built on information and data gathered from past outbreaks. However, epidemic outbreaks are never captured in statistical data alone but are communicated by narratives, supported by empirical observations. Outbreak reports discuss correlations between populations, locations and the disease to infer insights into causes, vectors and potential interventions. The problem with these narratives is usually the lack of consistent structure or strong conventions, which prohibit their formal analysis in larger corpora. Our interdisciplinary research investigates more than 100 reports from the third plague pandemic (1894-1952) evaluating ways of building a corpus to extract and structure this narrative information through text mining and manual annotation. In this paper we discuss the progress of our ongoing exploratory project, how we enhance optical character recognition (OCR) methods to improve text capture, our approach to structure the narratives and identify relevant entities in the reports. The structured corpus is made available via Solr enabling search and analysis across the whole collection for future research dedicated, for example, to the identification of concepts. We show preliminary visualisations of the characteristics of causation and differences with respect to gender as a result of syntactic-category-dependent corpus statistics. Our goal is to develop structured accounts of some of the most significant concepts that were used to understand the epidemiology of the third plague pandemic around the globe. The corpus enables researchers to analyse the reports collectively allowing for deep insights into the global epidemiological consideration of plague in the early twentieth century.

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