• Adrijana Car – Thomas Jekel – Josef Strobl – Gerald Griesebner (Eds.)

GI_Forum 2018, Volume 6, Issue 1

Journal for Geographic Information Science

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Verlag der Österreichischen Akademie der Wissenschaften
Austrian Academy of Sciences Press
A-1011 Wien, Dr. Ignaz Seipel-Platz 2
Tel. +43-1-515 81/DW 3420, Fax +43-1-515 81/DW 3400
https://verlag.oeaw.ac.at, e-mail: verlag@oeaw.ac.at

GI_Forum publishes high quality original research across the transdisciplinary field of Geographic Information Science (GIScience). The journal provides a platform for dialogue among GI-Scientists and educators, technologists and critical thinkers in an ongoing effort to advance the field and ultimately contribute to the creation of an informed GISociety. Submissions concentrate on innovation in education, science, methodology and technologies in the spatial domain and their role towards a more just, ethical and sustainable science and society. GI_Forum implements the policy of open access publication after a double-blind peer review process through a highly international team of seasoned scientists for quality assurance. Special emphasis is put on actively supporting young scientists through formative reviews of their submissions. Only English language contributions are published.

Starting 2016, GI_Forum publishes two issues a Year.
Joumal Information is available at: GI-Forum
GI_Forum is listed on the Directory of Open Access Journals (DOAJ)

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GI_Forum 2018, Volume 6, Issue 1

ISSN 2308-1708
Online Edition

ISBN 978-3-7001-8359-4
Online Edition



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Verlag der Österreichischen Akademie der Wissenschaften
Austrian Academy of Sciences Press
A-1011 Wien, Dr. Ignaz Seipel-Platz 2,
Tel. +43-1-515 81/DW 3420, Fax +43-1-515 81/DW 3400
https://verlag.oeaw.ac.at, e-mail: bestellung.verlag@oeaw.ac.at
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Talking about Places:Considering Context for the Geolocation of Images Extracted from Tweets

    Chiara Francalanci, Barbara Pernici, Gabriele Scalia, Gunter Zeug

GI_Forum 2018, Volume 6, Issue 1, pp. 243-250, 2018/06/22

Journal for Geographic Information Science

doi: 10.1553/giscience2018_01_s243

doi: 10.1553/giscience2018_01_s243


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doi:10.1553/giscience2018_01_s243



doi:10.1553/giscience2018_01_s243

Abstract

This paper investigates the extraction of geolocated images from social media. Pictures taken with a mobile device are typically georeferenced, but social media may or may not provide geo-coordinates, depending on their privacy policies. Our goal is to geolocate images extracted from Twitter to support emergency services in natural disasters. As the number of tweets with native georeferences is limited, we introduce algorithms that take advantage of various contextual clues included in social media posts to help increase the proportion of posts that can be geolocated. Using an explorative approach, we also investigate how to locate, in other social media, images that were originally embedded in tweets. The application of these context-based algorithms to a case study is discussed.

Keywords: tweet geolocation, context modelling, emergency mapping

Published Online: 2018/06/22 07:56:00

Object Identifier: 0xc1aa5572 0x00390ce0

Document viewed: Calculating...

Rights: https://creativecommons.org/licenses/by-nd/4.0/