Geographical Exploration and Analysis Extended to Textual Content (Short Paper)

Authors Raphaël Ceré, Mattia Egloff, François Bavaud

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Raphaël Ceré
  • Department of Geography and Sustainability, University of Lausanne, Switzerland
Mattia Egloff
  • Department of Language and Information Sciences, University of Lausanne, Switzerland
François Bavaud
  • Department of Language and Information Sciences & Department of Geography and Sustainability, University of Lausanne, Switzerland

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Raphaël Ceré, Mattia Egloff, and François Bavaud. Geographical Exploration and Analysis Extended to Textual Content (Short Paper). In 10th International Conference on Geographic Information Science (GIScience 2018). Leibniz International Proceedings in Informatics (LIPIcs), Volume 114, pp. 23:1-23:7, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2018)


Textual and socio-economical regional features can be integrated and merged by linearly combining the between-regions corresponding dissimilarities. The scheme accommodates for various squared Euclidean socio-economical and textual dissimilarities (such as chi2 or cosine dissimilarities derived from document-term matrix or topic modelling). Also, spatial configuration of the regions can be represented by a weighted unoriented network whose vertex weights match the relative importance of regions. Association between the network and the dissimilarities expresses in the multivariate spatial autocorrelation index delta, generalizing Moran's I, whose local version can be cartographied. Our case study bears on the Wikipedia notices and socio-economic profiles for the 2251 Swiss municipalities, whose weights (socio-economical or textual) can be freely chosen.

Subject Classification

ACM Subject Classification
  • Mathematics of computing → Probability and statistics
  • Information systems → Clustering
  • Spatial autocorrelation
  • Weighted spatial network
  • Document-term matrix
  • Multivariate features
  • Soft clustering


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