GI_Forum 2016, Volume 4, 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 |
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DATUM, UNTERSCHRIFT / DATE, SIGNATURE
BANK AUSTRIA CREDITANSTALT, WIEN (IBAN AT04 1100 0006 2280 0100, BIC BKAUATWW), DEUTSCHE BANK MÜNCHEN (IBAN DE16 7007 0024 0238 8270 00, BIC DEUTDEDBMUC)
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GI_Forum 2016, Volume 4, Issue 1 Journal for Geographic Information Science
ISSN 2308-1708 Online Edition ISBN 978-3-7001-7988-7 Online Edition
Sreten Cvetojevic,
Levente Juhasz,
Hartwig Hochmair
S. 191 - 203 doi:10.1553/giscience2016_01_s191 Verlag der Österreichischen Akademie der Wissenschaften
Abstract: Twitter and Instagram are social networking services that allow users to share images. To some extent, both platforms provide means for the user to annotate images with geographic location information. Using a selection of images shared through these two platforms, this study compares the photographer’s position, which is manually estimated from the scene in the image, with the annotated location information associated with the image and the position of the object being photographed. This approach provides an initial insight into the Twitter user’s movement between the location where a picture is taken and the place from where it is uploaded to Twitter. Furthermore, the distance between the photographer’s position and the location of the object shown in a Twitter or Instagram photograph can be used to assess the visual prominence of a photographed urban object in relation to its surroundings. Finally, the dataset generated in the research allows us to assess the positional accuracy of location labels in Instagram through comparison of the label position and the true position of the referenced object. For each of the different analyses, this paper discusses sources that could potentially lead to positional errors of images in Twitter and Instagram, and provides a comprehensive set of illustrative examples from different cities. Keywords: volunteered geographic information, social media image, positional accuracy, data quality Published Online: 2016/06/29 09:23:21 Object Identifier: 0xc1aa5576 0x0033ff9f Rights:https://creativecommons.org/licenses/by-nd/4.0/
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.
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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 |