Slicing and Dicing a Newspaper Corpus for Historical Ecology Research

Marieke van Erp, Jesse de Does, Katrien Depuydt, Rob Lenders, Thomas van Goethem

Onderzoeksoutput: Hoofdstuk in boek/boekdeelBijdrage aan conferentie proceedingsWetenschappelijkpeer review

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Historical newspapers are a novel source of information for historical ecologists to study the interactions between humans and animals through time and space. Newspaper archives are particularly interesting to analyse because of their breadth and depth. However, the size and the occasional noisiness of such archives also brings difficulties, as manual analysis is impossible. In this paper, we present experiments and results on automatic query expansion and categorisation for the perception of animal species between 1800 and 1940. For query expansion and to the manual annotation process, we used lexicons. For the categorisation we trained a Support Vector Machine model. Our results indicate that we can distinguish newspaper articles that are about animal species from those that are not with an F 1 of 0.92 and the subcategorisation of the different types of newspapers on animals up to 0.84 F 1 .
Originele taal-2Engels
Titel Knowledge Engineering and Knowledge Management
UitgeverijSpringer Verlag GmbH
Pagina's470-484
StatusGepubliceerd - 2018

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