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

Ceré, Raphaël; Egloff, Mattia; Bavaud, François

doi:10.4230/LIPIcs.GISCIENCE.2018.23

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Document Identifiers

DOI: 10.4230/LIPIcs.GISCIENCE.2018.23
URN: urn:nbn:de:0030-drops-93514

Author Details

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

Cite AsGet BibTex

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)
https://doi.org/10.4230/LIPIcs.GISCIENCE.2018.23

Abstract

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

Keywords

Spatial autocorrelation
Weighted spatial network
Document-term matrix
Multivariate features
Soft clustering

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