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GeoCorpora: building a corpus to test and train microblog geoparsers

Authors:

Jan Oliver Wallgrün,

Morteza Karimzadeh,

Alan M. MacEachren,

Scott PezanowskiAuthors Info & Claims

International Journal of Geographical Information Science, Volume 32, Issue 1

Pages 1 - 29

https://doi.org/10.1080/13658816.2017.1368523

Published: 01 January 2018 Publication History

Abstract

In this article, we present the GeoCorpora corpus building framework and software tools as well as a geo-annotated Twitter corpus built with these tools to foster research and development in the areas of microblog/Twitter geoparsing and geographic information retrieval. The developed framework employs crowdsourcing and geovisual analytics to support the construction of large corpora of text in which the mentioned location entities are identified and geolocated to toponyms in existing geographical gazetteers. We describe how the approach has been applied to build a corpus of geo-annotated tweets that will be made freely available to the research community alongside this article to support the evaluation, comparison and training of geoparsers. Additionally, we report lessons learned related to corpus construction for geoparsing as well as insights about the notions of place and natural spatial language that we derive from application of the framework to building this corpus.

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Mai GHuang WSun JSong SMishra DLiu NGao SLiu TCong GHu YCundy CLi ZZhu RLao N(2024)On the Opportunities and Challenges of Foundation Models for GeoAI (Vision Paper)ACM Transactions on Spatial Algorithms and Systems10.1145/365307010:2(1-46)Online publication date: 1-Jul-2024
https://dl.acm.org/doi/10.1145/3653070
Koshy RElango S(2024)Applying social media in emergency response: an attention-based bidirectional deep learning system for location reference recognition in disaster tweetsApplied Intelligence10.1007/s10489-024-05462-654:7(5768-5793)Online publication date: 1-Apr-2024
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Hu XZhou ZLi HHu YGu FKersten JFan HKlan F(2023)Location Reference Recognition from Texts: A Survey and ComparisonACM Computing Surveys10.1145/362581956:5(1-37)Online publication date: 27-Nov-2023
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Published In

International Journal of Geographical Information Science Volume 32, Issue 1

January 2018

212 pages

ISSN:1365-8816

EISSN:1365-8824

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Taylor & Francis, Inc.

United States

Publication History

Published: 01 January 2018

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Mai GHuang WSun JSong SMishra DLiu NGao SLiu TCong GHu YCundy CLi ZZhu RLao N(2024)On the Opportunities and Challenges of Foundation Models for GeoAI (Vision Paper)ACM Transactions on Spatial Algorithms and Systems10.1145/365307010:2(1-46)Online publication date: 1-Jul-2024
https://dl.acm.org/doi/10.1145/3653070
Koshy RElango S(2024)Applying social media in emergency response: an attention-based bidirectional deep learning system for location reference recognition in disaster tweetsApplied Intelligence10.1007/s10489-024-05462-654:7(5768-5793)Online publication date: 1-Apr-2024
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Gritta MPilehvar MCollier N(2020)A pragmatic guide to geoparsing evaluationLanguage Resources and Evaluation10.1007/s10579-019-09475-354:3(683-712)Online publication date: 1-Sep-2020
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Hu Y(2018)EUPEGProceedings of the 12th Workshop on Geographic Information Retrieval10.1145/3281354.3281357(1-2)Online publication date: 6-Nov-2018
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Chesnokova OPurves R(2018)Automatically creating a spatially referenced corpus of landscape perceptionProceedings of the 12th Workshop on Geographic Information Retrieval10.1145/3281354.3281356(1-2)Online publication date: 6-Nov-2018
https://dl.acm.org/doi/10.1145/3281354.3281356

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