License: 
Creative Commons Attribution 3.0 Unported license (CC BY 3.0)
When quoting this document, please refer to the following
DOI: 10.4230/LIPIcs.GISCIENCE.2018.44
URN: urn:nbn:de:0030-drops-93720
URL: http://dagstuhl.sunsite.rwth-aachen.de/volltexte/2018/9372/
MacEachren, Alan M. ;
Caneba, Richard ;
Chen, Hanzhou ;
Cole, Harrison ;
Domanico, Emily ;
Triozzi, Nicholas ;
Xu, Fangcao ;
Yang, Liping
Is This Statement About A Place? Comparing two perspectives (Short Paper)
Abstract
Text often includes references to places by name; in prior work, more than 20% of a sample of event-related tweets were found to include place names. Research has addressed the challenge of leveraging the geographic data reflected in text statements, with well-developed methods to recognize location mentions in text and related work on automated toponym resolution (deciding which place in the world is meant by a place name). A core issue that remains is to distinguish between text that mentions a place or places and text that is about a place or places. This paper presents the first step in research to address this challenge. The research reported here sets the conceptual and practical groundwork for subsequent supervised machine learning research; that research will leverage human-produced training data, for which a judgment is made about whether a statement is or is not about a place (or places), to train computational methods to do this classification for large volumes of text. The research step presented here focuses on three questions: (1) what kinds of entities are typically conceptualized as places, (2) what features of a statement prompt the reader to judge a statement to be about a place (or not about a place) and (3) how do judgments of whether or not a statement is about a place compare between a group of experts who have studied the concept of "place" from a geographic perspective and a cross-section of individuals recruited through a crowdsourcing platform to make these judgments.
BibTeX - Entry
@InProceedings{maceachren_et_al:LIPIcs:2018:9372,
author = {Alan M. MacEachren and Richard Caneba and Hanzhou Chen and Harrison Cole and Emily Domanico and Nicholas Triozzi and Fangcao Xu and Liping Yang},
title = {{Is This Statement About A Placel Comparing two perspectives (Short Paper)}},
booktitle = {10th International Conference on Geographic Information Science (GIScience 2018)},
pages = {44:1--44:6},
series = {Leibniz International Proceedings in Informatics (LIPIcs)},
ISBN = {978-3-95977-083-5},
ISSN = {1868-8969},
year = {2018},
volume = {114},
editor = {Stephan Winter and Amy Griffin and Monika Sester},
publisher = {Schloss Dagstuhl--Leibniz-Zentrum fuer Informatik},
address = {Dagstuhl, Germany},
URL = {http://drops.dagstuhl.de/opus/volltexte/2018/9372},
URN = {urn:nbn:de:0030-drops-93720},
doi = {10.4230/LIPIcs.GISCIENCE.2018.44},
annote = {Keywords: geographic information retrieval, spatial language, crowdsourcing}
}
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Keywords: |
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geographic information retrieval, spatial language, crowdsourcing |
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Collection: |
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10th International Conference on Geographic Information Science (GIScience 2018) |
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Issue Date: |
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2018 |
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Date of publication: |
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02.08.2018 |
