License: Creative Commons Attribution 3.0 Unported license (CC BY 3.0)
When quoting this document, please refer to the following
DOI: 10.4230/LIPIcs.GISCIENCE.2018.23
URN: urn:nbn:de:0030-drops-93514
URL: http://dagstuhl.sunsite.rwth-aachen.de/volltexte/2018/9351/
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Ceré, Raphaël ; Egloff, Mattia ; Bavaud, François

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

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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.

BibTeX - Entry

@InProceedings{cer_et_al:LIPIcs:2018:9351,
  author =	{Rapha{\"e}l Cer{\'e} and Mattia Egloff and Fran{\c{c}}ois Bavaud},
  title =	{{Geographical Exploration and Analysis Extended to Textual Content (Short Paper)}},
  booktitle =	{10th International Conference on Geographic Information  Science (GIScience 2018)},
  pages =	{23:1--23:7},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-083-5},
  ISSN =	{1868-8969},
  year =	{2018},
  volume =	{114},
  editor =	{Stephan Winter and Amy Griffin and Monika Sester},
  publisher =	{Schloss Dagstuhl--Leibniz-Zentrum fuer Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{http://drops.dagstuhl.de/opus/volltexte/2018/9351},
  URN =		{urn:nbn:de:0030-drops-93514},
  doi =		{10.4230/LIPIcs.GISCIENCE.2018.23},
  annote =	{Keywords: Spatial autocorrelation, Weighted spatial network, Document-term matrix, Multivariate features, Soft clustering}
}

Keywords: Spatial autocorrelation, Weighted spatial network, Document-term matrix, Multivariate features, Soft clustering
Collection: 10th International Conference on Geographic Information Science (GIScience 2018)
Issue Date: 2018
Date of publication: 02.08.2018

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