Geo-Information Harvesting from Social Media Data
As unconventional sources of geo-information, massive imagery and text messages from open platforms and social media form a temporally quasi-seamless, spatially multi-perspective stream, but with unknown and diverse quality. Due to its complementarity to remote sensing data, geo-information from the...
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creator | Zhu, Xiao Xiang Wang, Yuanyuan Kochupillai, Mrinalini Werner, Martin Häberle, Matthias Hoffmann, Eike Jens Taubenböck, Hannes Tuia, Devis Levering, Alex Jacobs, Nathan Kruspe, Anna Abdulahhad, Karam |
description | As unconventional sources of geo-information, massive imagery and text
messages from open platforms and social media form a temporally quasi-seamless,
spatially multi-perspective stream, but with unknown and diverse quality. Due
to its complementarity to remote sensing data, geo-information from these
sources offers promising perspectives, but harvesting is not trivial due to its
data characteristics. In this article, we address key aspects in the field,
including data availability, analysis-ready data preparation and data
management, geo-information extraction from social media text messages and
images, and the fusion of social media and remote sensing data. We then
showcase some exemplary geographic applications. In addition, we present the
first extensive discussion of ethical considerations of social media data in
the context of geo-information harvesting and geographic applications. With
this effort, we wish to stimulate curiosity and lay the groundwork for
researchers who intend to explore social media data for geo-applications. We
encourage the community to join forces by sharing their code and data. |
doi_str_mv | 10.48550/arxiv.2211.00543 |
format | Article |
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messages from open platforms and social media form a temporally quasi-seamless,
spatially multi-perspective stream, but with unknown and diverse quality. Due
to its complementarity to remote sensing data, geo-information from these
sources offers promising perspectives, but harvesting is not trivial due to its
data characteristics. In this article, we address key aspects in the field,
including data availability, analysis-ready data preparation and data
management, geo-information extraction from social media text messages and
images, and the fusion of social media and remote sensing data. We then
showcase some exemplary geographic applications. In addition, we present the
first extensive discussion of ethical considerations of social media data in
the context of geo-information harvesting and geographic applications. With
this effort, we wish to stimulate curiosity and lay the groundwork for
researchers who intend to explore social media data for geo-applications. We
encourage the community to join forces by sharing their code and data.</description><identifier>DOI: 10.48550/arxiv.2211.00543</identifier><language>eng</language><subject>Computer Science - Computer Vision and Pattern Recognition</subject><creationdate>2022-11</creationdate><rights>http://creativecommons.org/licenses/by/4.0</rights><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>228,230,780,885</link.rule.ids><linktorsrc>$$Uhttps://arxiv.org/abs/2211.00543$$EView_record_in_Cornell_University$$FView_record_in_$$GCornell_University$$Hfree_for_read</linktorsrc><backlink>$$Uhttps://doi.org/10.48550/arXiv.2211.00543$$DView paper in arXiv$$Hfree_for_read</backlink></links><search><creatorcontrib>Zhu, Xiao Xiang</creatorcontrib><creatorcontrib>Wang, Yuanyuan</creatorcontrib><creatorcontrib>Kochupillai, Mrinalini</creatorcontrib><creatorcontrib>Werner, Martin</creatorcontrib><creatorcontrib>Häberle, Matthias</creatorcontrib><creatorcontrib>Hoffmann, Eike Jens</creatorcontrib><creatorcontrib>Taubenböck, Hannes</creatorcontrib><creatorcontrib>Tuia, Devis</creatorcontrib><creatorcontrib>Levering, Alex</creatorcontrib><creatorcontrib>Jacobs, Nathan</creatorcontrib><creatorcontrib>Kruspe, Anna</creatorcontrib><creatorcontrib>Abdulahhad, Karam</creatorcontrib><title>Geo-Information Harvesting from Social Media Data</title><description>As unconventional sources of geo-information, massive imagery and text
messages from open platforms and social media form a temporally quasi-seamless,
spatially multi-perspective stream, but with unknown and diverse quality. Due
to its complementarity to remote sensing data, geo-information from these
sources offers promising perspectives, but harvesting is not trivial due to its
data characteristics. In this article, we address key aspects in the field,
including data availability, analysis-ready data preparation and data
management, geo-information extraction from social media text messages and
images, and the fusion of social media and remote sensing data. We then
showcase some exemplary geographic applications. In addition, we present the
first extensive discussion of ethical considerations of social media data in
the context of geo-information harvesting and geographic applications. With
this effort, we wish to stimulate curiosity and lay the groundwork for
researchers who intend to explore social media data for geo-applications. We
encourage the community to join forces by sharing their code and data.</description><subject>Computer Science - Computer Vision and Pattern Recognition</subject><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2022</creationdate><recordtype>article</recordtype><sourceid>GOX</sourceid><recordid>eNotzruOwjAQhWE3FAj2AajwCyQ7zmDHKVGWmwSigD4afEGWSIxMhODtdxeoTvPr6GNsIiCfaSnhm9Ij3POiECIHkDMcMrFyMdt0PqaW-hA7vqZ0d7c-dGfuU2z5IZpAF75zNhD_oZ7GbODpcnNfnx2x43JxrNfZdr_a1PNtRqrEDFXlyRhBDkvlUFvvT1pQgQbQyLJCZdBZhaX8ywCM8xqEBXnS1lr0Akds-r59mZtrCi2lZ_Nvb152_AVgKT53</recordid><startdate>20221101</startdate><enddate>20221101</enddate><creator>Zhu, Xiao Xiang</creator><creator>Wang, Yuanyuan</creator><creator>Kochupillai, Mrinalini</creator><creator>Werner, Martin</creator><creator>Häberle, Matthias</creator><creator>Hoffmann, Eike Jens</creator><creator>Taubenböck, Hannes</creator><creator>Tuia, Devis</creator><creator>Levering, Alex</creator><creator>Jacobs, Nathan</creator><creator>Kruspe, Anna</creator><creator>Abdulahhad, Karam</creator><scope>AKY</scope><scope>GOX</scope></search><sort><creationdate>20221101</creationdate><title>Geo-Information Harvesting from Social Media Data</title><author>Zhu, Xiao Xiang ; Wang, Yuanyuan ; Kochupillai, Mrinalini ; Werner, Martin ; Häberle, Matthias ; Hoffmann, Eike Jens ; Taubenböck, Hannes ; Tuia, Devis ; Levering, Alex ; Jacobs, Nathan ; Kruspe, Anna ; Abdulahhad, Karam</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-a673-369facc1ae376e38dffb81a23c03c57936c3ed6375fac00cef801d05b8ddd3f13</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2022</creationdate><topic>Computer Science - Computer Vision and Pattern Recognition</topic><toplevel>online_resources</toplevel><creatorcontrib>Zhu, Xiao Xiang</creatorcontrib><creatorcontrib>Wang, Yuanyuan</creatorcontrib><creatorcontrib>Kochupillai, Mrinalini</creatorcontrib><creatorcontrib>Werner, Martin</creatorcontrib><creatorcontrib>Häberle, Matthias</creatorcontrib><creatorcontrib>Hoffmann, Eike Jens</creatorcontrib><creatorcontrib>Taubenböck, Hannes</creatorcontrib><creatorcontrib>Tuia, Devis</creatorcontrib><creatorcontrib>Levering, Alex</creatorcontrib><creatorcontrib>Jacobs, Nathan</creatorcontrib><creatorcontrib>Kruspe, Anna</creatorcontrib><creatorcontrib>Abdulahhad, Karam</creatorcontrib><collection>arXiv Computer Science</collection><collection>arXiv.org</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>Zhu, Xiao Xiang</au><au>Wang, Yuanyuan</au><au>Kochupillai, Mrinalini</au><au>Werner, Martin</au><au>Häberle, Matthias</au><au>Hoffmann, Eike Jens</au><au>Taubenböck, Hannes</au><au>Tuia, Devis</au><au>Levering, Alex</au><au>Jacobs, Nathan</au><au>Kruspe, Anna</au><au>Abdulahhad, Karam</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Geo-Information Harvesting from Social Media Data</atitle><date>2022-11-01</date><risdate>2022</risdate><abstract>As unconventional sources of geo-information, massive imagery and text
messages from open platforms and social media form a temporally quasi-seamless,
spatially multi-perspective stream, but with unknown and diverse quality. Due
to its complementarity to remote sensing data, geo-information from these
sources offers promising perspectives, but harvesting is not trivial due to its
data characteristics. In this article, we address key aspects in the field,
including data availability, analysis-ready data preparation and data
management, geo-information extraction from social media text messages and
images, and the fusion of social media and remote sensing data. We then
showcase some exemplary geographic applications. In addition, we present the
first extensive discussion of ethical considerations of social media data in
the context of geo-information harvesting and geographic applications. With
this effort, we wish to stimulate curiosity and lay the groundwork for
researchers who intend to explore social media data for geo-applications. We
encourage the community to join forces by sharing their code and data.</abstract><doi>10.48550/arxiv.2211.00543</doi><oa>free_for_read</oa></addata></record> |
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subjects | Computer Science - Computer Vision and Pattern Recognition |
title | Geo-Information Harvesting from Social Media Data |
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