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A framework for annotating OpenStreetMap objects using geo-tagged tweets

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A Correction to this article was published on 11 August 2018

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Abstract

Recent years have witnessed an explosion of geospatial data, especially in the form of Volunteered Geographic Information (VGI). As a prominent example, OpenStreetMap (OSM) creates a free editable map of the world from a large number of contributors. On the other hand, social media platforms such as Twitter or Instagram supply dynamic social feeds at population level. As much of such data is geo-tagged, there is a high potential on integrating social media with OSM to enrich OSM with semantic annotations, which will complement existing objective description oriented annotations to provide a broader range of annotations. In this paper, we propose a comprehensive framework on integrating social media data and VGI data to derive knowledge about geographical objects, specifically, top relevant annotations from tweets for objects in OSM. We first integrate geo-tagged tweets with OSM data with scalable spatial queries running on MapReduce. We propose a frequency based method for annotating boundary based geographic objects (a polygon), and a probability based method for annotating point based geographic objects (Latitude and Longitude), with consideration of noise. We evaluate our methods using a large geo-tagged tweets corpus and representative geographic objects from OSM, which demonstrates promising results through ground-truth comparison and case studies. We are able to produce up to 80% correct names for geographical objects and discover implicitly relevant information, such as popular exhibitions of a museum, the nicknames or visitors’ impression to a tourism attraction.

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Change history

  • 11 August 2018

    The original version of this article contained two errors.

Notes

  1. Openstreetmap. www.openstreetmap.org.

  2. Wikimapia API. wikimapia.org/api.

  3. https://www.quora.com/What-percentage-of-tweets-are-geotagged-What-percentage-of-geotagged-tweets-are-ascribed-to-a-venue

  4. http://thenextweb.com/2010/01/15/twitter-geofail-023-tweets-geotagged

  5. http://taginfo.openstreetmap.org/

  6. http://planet.openstreetmap.org/

  7. The two original tweets for “architecture” are: #imperialwarmuseumnorth #manchester #salfordquays ... Impressive architecture #lovemanchester https://t.co/eS4tfRkEqo and The walls between art and engineering exist only in our minds #bridge #architecture #manchester https://t.co/SVndM4ARCk

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Authors and Affiliations

  1. Department of Computer Science, Stony Brook University, Stony Brook, NY, USA

    Xin Chen, Hoang Vo, Yu Wang & Fusheng Wang

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  1. Xin Chen
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  2. Hoang Vo
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  3. Yu Wang
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  4. Fusheng Wang
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Correspondence to Xin Chen.

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Chen, X., Vo, H., Wang, Y. et al. A framework for annotating OpenStreetMap objects using geo-tagged tweets. Geoinformatica 22, 589–613 (2018). https://doi.org/10.1007/s10707-018-0323-8

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  • DOI: https://doi.org/10.1007/s10707-018-0323-8

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