The GeoNewsMiner: An interactive spatial humanities tool to visualize geographical references in historical newspapers
Creators: name: Viola, Lorella
name: Verheul, Jaap
Publisher: name: unknown
Year: 2020
Subjects: subject: Machine learning
subject: Immigrants' writings
subject: Identity (Psychology)

description: The GeoNewsMiner (GNM) is an interactive tool that maps and visualizes geographical references in historical newspapers. As a use case, we analysed Italian immigrant newspapers published in the United States from 1898 to 1920, as collected in the corpus ChroniclItaly (Viola 2018). In order to offer new perspectives on the geographies of the past, we employed a state-of-the-art deep learning method to extract and disambiguate place names from historical newspapers. The two major advantages lie in its potential for text enriching: 1) they may be based on the historical context of a historical corpus; 2) they are able to recognize toponyms in a dynamic way, for instance as a geographical concept (Viola and Verheul 2020). For the development of the GNM, we used the deep learning sequence tagging tool developed by Riedl and Padó (2018). Afterwards, locations were geocoded by using the Google API. The tagged version of ChroniclItaly is available as an OA resource (ChroniclItaly 2.0, Viola 2019). 
Finally, to visualise and explore the data, we developed the GNM App. Unique to this tool is the possibility to aggregate the data according to a wide range of parameters (time; newspaper's title; least/most mentioned places; absolute or relative frequency; aggregation on national, regional or city level). It is also possible to overlay historical maps that show the borders of selected years (1880, 1914, 1920, 1994), and download and share the data/results. One potential application of GNM is for example the possibility to reconstruct the "geographical agenda" of historical newspapers by analysing the changing geographical bias of the press. The full documentation of GNM is made available to the research community to facilitate transparency, reproducibility and replicability (Viola 2020). The app has much to recommend particularly to humanities scholars who are more and more confronted with the challenge of exploring collections larger than before and in a digital format.
description: The GeoNewsMiner (GNM) is an interactive tool that maps and visualizes geographical references in historical newspapers. As a use case, we analysed Italian immigrant newspapers published in the United States from 1898 to 1920, as collected in the corpus ChroniclItaly (Viola 2018). In order to offer new perspectives on the geographies of the past, we employed a state-of-the-art deep learning method to extract and disambiguate place names from historical newspapers. The two major advantages lie in its potential for text enriching: 1) they may be based on the historical context of a historical corpus; 2) they are able to recognize toponyms in a dynamic way, for instance as a geographical concept (Viola and Verheul 2020). For the development of the GNM, we used the deep learning sequence tagging tool developed by Riedl and Padó (2018). Afterwards, locations were geocoded by using the Google API. The tagged version of ChroniclItaly is available as an OA resource (ChroniclItaly 2.0, Viola 2019). Finally, to visualise and explore the data, we developed the GNM App. Unique to this tool is the possibility to aggregate the data according to a wide range of parameters (time; newspaper's title; least/most mentioned places; absolute or relative frequency; aggregation on national, regional or city level). It is also possible to overlay historical maps that show the borders of selected years (1880, 1914, 1920, 1994), and download and share the data/results. One potential application of GNM is for example the possibility to reconstruct the "geographical agenda" of historical newspapers by analysing the changing geographical bias of the press. The full documentation of GNM is made available to the research community to facilitate transparency, reproducibility and replicability (Viola 2020). The app has much to recommend particularly to humanities scholars who are more and more confronted with the challenge of exploring collections larger than before and in a digital format.