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Geospatiality: the effect of topics on the presence of geolocation in English text data.

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Title: Geospatiality: the effect of topics on the presence of geolocation in English text data.
Authors: Mast, Johannes1 (AUTHOR) Johannes.mast@dlr.de, Lemoine-Rodríguez, Richard2,3 (AUTHOR), Rittlinger, Vanessa1 (AUTHOR), Mühlbauer, Martin1 (AUTHOR), Biewer, Carolin3,4 (AUTHOR), Geiß, Christian1,5 (AUTHOR), Taubenböck, Hannes1,2,3 (AUTHOR)
Source: International Journal of Geographical Information Science. Mar2026, Vol. 40 Issue 3, p868-899. 32p.
Subjects: Location data, Geographic spatial analysis, English language writing, Tourism, Twitter (Web resource), Statistical bias, Corpora
Abstract: Geolocated text data are a promising data source for spatial analyses in many fields, from disease surveillance to the spatial humanities. This study investigates the relationship between texts' thematic categories and their likelihood of containing usable geolocation information by quantifying and modelling this relationship across seven diverse English text datasets of different types, including web forums, microblogs, news, and magazines. We find that the likelihood of geoinformation is highly variant, being high for the category 'Travel, Tourism & Migration' and low for 'Private Life, Family & Relationships'. The rank-correlation of this likelihood between datasets is moderate to strong. These findings indicate that the topic plays a significant role in determining the frequency of geospatial references within the text, and that the effect is not entirely dataset-specific. This contributes to the empirical study of the concept of spatiality and provides valuable insights for bias mitigation in the increasing use of text as data for spatial analyses. [ABSTRACT FROM AUTHOR]
Copyright of International Journal of Geographical Information Science is the property of Taylor & Francis Ltd and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Database: Engineering Source
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DbLabel: Engineering Source
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  Data: Geospatiality: the effect of topics on the presence of geolocation in English text data.
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  Data: <searchLink fieldCode="AR" term="%22Mast%2C+Johannes%22">Mast, Johannes</searchLink><relatesTo>1</relatesTo> (AUTHOR)<i> Johannes.mast@dlr.de</i><br /><searchLink fieldCode="AR" term="%22Lemoine-Rodríguez%2C+Richard%22">Lemoine-Rodríguez, Richard</searchLink><relatesTo>2,3</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Rittlinger%2C+Vanessa%22">Rittlinger, Vanessa</searchLink><relatesTo>1</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Mühlbauer%2C+Martin%22">Mühlbauer, Martin</searchLink><relatesTo>1</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Biewer%2C+Carolin%22">Biewer, Carolin</searchLink><relatesTo>3,4</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Geiß%2C+Christian%22">Geiß, Christian</searchLink><relatesTo>1,5</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Taubenböck%2C+Hannes%22">Taubenböck, Hannes</searchLink><relatesTo>1,2,3</relatesTo> (AUTHOR)
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  Data: <searchLink fieldCode="JN" term="%22International+Journal+of+Geographical+Information+Science%22">International Journal of Geographical Information Science</searchLink>. Mar2026, Vol. 40 Issue 3, p868-899. 32p.
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  Data: <searchLink fieldCode="DE" term="%22Location+data%22">Location data</searchLink><br /><searchLink fieldCode="DE" term="%22Geographic+spatial+analysis%22">Geographic spatial analysis</searchLink><br /><searchLink fieldCode="DE" term="%22English+language+writing%22">English language writing</searchLink><br /><searchLink fieldCode="DE" term="%22Tourism%22">Tourism</searchLink><br /><searchLink fieldCode="DE" term="%22Twitter+%28Web+resource%29%22">Twitter (Web resource)</searchLink><br /><searchLink fieldCode="DE" term="%22Statistical+bias%22">Statistical bias</searchLink><br /><searchLink fieldCode="DE" term="%22Corpora%22">Corpora</searchLink>
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  Label: Abstract
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  Data: Geolocated text data are a promising data source for spatial analyses in many fields, from disease surveillance to the spatial humanities. This study investigates the relationship between texts' thematic categories and their likelihood of containing usable geolocation information by quantifying and modelling this relationship across seven diverse English text datasets of different types, including web forums, microblogs, news, and magazines. We find that the likelihood of geoinformation is highly variant, being high for the category 'Travel, Tourism & Migration' and low for 'Private Life, Family & Relationships'. The rank-correlation of this likelihood between datasets is moderate to strong. These findings indicate that the topic plays a significant role in determining the frequency of geospatial references within the text, and that the effect is not entirely dataset-specific. This contributes to the empirical study of the concept of spatiality and provides valuable insights for bias mitigation in the increasing use of text as data for spatial analyses. [ABSTRACT FROM AUTHOR]
– Name: AbstractSuppliedCopyright
  Label:
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  Data: <i>Copyright of International Journal of Geographical Information Science is the property of Taylor & Francis Ltd and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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        Value: 10.1080/13658816.2025.2460051
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      – Code: eng
        Text: English
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        PageCount: 32
        StartPage: 868
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        Type: general
      – SubjectFull: Geographic spatial analysis
        Type: general
      – SubjectFull: English language writing
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      – SubjectFull: Tourism
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      – SubjectFull: Twitter (Web resource)
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      – SubjectFull: Statistical bias
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      – SubjectFull: Corpora
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      – TitleFull: Geospatiality: the effect of topics on the presence of geolocation in English text data.
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              Text: Mar2026
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              Y: 2026
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