Abstract
Previous studies have highlighted the importance of having long term
data for the study of cities, but such sources are relatively scarce.
This is especially the case for data about relations between cities,
which is a crucial aspect of urban dynamics. Over the last two decades,
many efforts have been made to digitalize texts, including books and
newspapers, which are primary sources on most of our societies.
Researchers have shown that these massive digital archives can be used
to identify macroscopic trends related to historical and cultural
changes. The wealth of geographic information in such digital archives
has not been used much, while they are very valuable for the study of
cities. In this paper, we present DIGGER, a newly developed dataset that
we built on Delpher, the digital archive of historical newspapers of
the National Library of the Netherlands, by extracting geographical
information from a selection of 102
million of news items. This dataset allowed us to study the spatial
diffusion of information on and between the Dutch cities from a corpus
of 81 newspapers published in 29 different cities between 1869 and 1994.
This paper presents the method developed to build the dataset as well
as the validation steps for the accuracy of the place name recognition.
This dataset can be used to study the evolution of the Dutch urban
system as well as aspects related to the spatial diffusion of
information and geographical bias in media coverage.
Original language | English |
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Article number | 928 |
Journal | Cybergeo |
DOIs | |
Publication status | Published - 14 Jan 2020 |
Keywords
- System of cities
- Flows
- Diffusion
- History
- Database
- Text mining
- Geocoding
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One century of information diffusion in the Netherlands derived from a massive digital archive of historical newspapers: the DIGGER dataset (dataset)
Peris, A. (Creator), Faber, W. J. (Creator), Meijers, E. (Creator) & Van Ham, M. (Creator), 4TU.ResearchData , 2019
https://data.4tu.nl/repository/uuid:a14a1607-dafe-4a8a-aebc-d1c5cd66a588
Dataset