Extracting and comparing places using geo-social media
Ostermann, F. O., Huang, H., Andrienko, G. , Andrienko, N., Capineri, C., Farkas, K. & Purves, R. S. (2015). Extracting and comparing places using geo-social media. In: Mallet, C, Paparoditis, N, Dowman, I , Elberink, SO, Raimond, AM, Rottensteiner, F, Yang, M, Christophe, S, Coltekin, A & Bredif, M (Eds.), ISPRS GEOSPATIAL WEEK 2015. ISPRS Geospatial Week 2015, 28 Sep - 3 Oct 2015, La Grande Motte, France. doi: 10.5194/isprsannals-II-3-W5-311-2015
Abstract
Increasing availability of Geo-Social Media (e.g. Facebook, Foursquare and Flickr) has led to the accumulation of large volumes of social media data. These data, especially geotagged ones, contain information about perception of and experiences in various environments. Harnessing these data can be used to provide a better understanding of the semantics of places. We are interested in the similarities or differences between different Geo-Social Media in the description of places. This extended abstract presents the results of a first step towards a more in-depth study of semantic similarity of places. Particularly, we took places extracted through spatio-temporal clustering from one data source (Twitter) and examined whether their structure is reflected semantically in another data set (Flickr). Based on that, we analyse how the semantic similarity between places varies over space and scale, and how Tobler's first law of geography holds with regards to scale and places.
Publication Type: | Conference or Workshop Item (Paper) |
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Publisher Keywords: | User-generated Geographic Content, Volunteered Geographic Information, Geo-social Media, Semantic Similarity, Geographic Places |
Subjects: | G Geography. Anthropology. Recreation > GA Mathematical geography. Cartography Q Science > QA Mathematics > QA75 Electronic computers. Computer science |
Departments: | School of Science & Technology > Computer Science School of Science & Technology > Computer Science > giCentre |
Available under License Creative Commons: Attribution 3.0.
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