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On Spatial Measures of Geographic Relevance for Geotagged Social Media Content

Wang, Xin; Gaugel, Tristan; Keller, Matthias

Abstract: Recently, geotagged social media contents became increasingly available to researchers and were subject to more and more studies. Different spatial measures such as Focus, Entropy and Spread have been applied to describe geospatial characteristics of social media contents. In this paper, we draw the attention to the fact that these popular measures do not necessarily show the geographic relevance or dependence of social content, but mix up geographic relevance, the distribution of the user population, and sample size. Therefore, results based on these measures cannot be interpreted as geographic effects alone. By means of an assessment, based on Twitter data collected over a time span of six weeks, we highlight potential misinterpretations and we furthermore propose normalized measures which show less dependency on the underlying user population and are able to mitigate the effect of outliers.


Zugehörige Institution(en) am KIT Institut für Telematik (TM)
Steinbuch Centre for Computing (SCC)
Publikationstyp Proceedingsbeitrag
Jahr 2016
Sprache Englisch
Identifikator DOI: 10.1007/978-3-319-29009-6_4
ISBN: 978-3-319-29008-9
ISSN: 0302-9743
KITopen ID: 1000052804
Erschienen in Big Data Analytics in the Social and Ubiquitous Context
Verlag Springer
Seiten 70-89
Serie Lecture Notes in Computer Science ; 9546
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