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An empirical evaluation of electronic annotation tools for Twitter data

Despite a growing number of natural language processing shared-tasks dedicated to the use of Twitter data, there is currently no ad-hoc annotation tool for the purpose. During the 6th edition of Biomedical Linked Annotation Hackathon (BLAH), after a short review of 19 generic annotation tools, we ad...

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Detalles Bibliográficos
Autores principales: Weissenbacher, Davy, O'Connor, Karen, Hiraki, Aiko T., Kim, Jin-Dong, Gonzalez-Hernandez, Graciela
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Korea Genome Organization 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7362942/
https://www.ncbi.nlm.nih.gov/pubmed/32634878
http://dx.doi.org/10.5808/GI.2020.18.2.e24
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author Weissenbacher, Davy
O'Connor, Karen
Hiraki, Aiko T.
Kim, Jin-Dong
Gonzalez-Hernandez, Graciela
author_facet Weissenbacher, Davy
O'Connor, Karen
Hiraki, Aiko T.
Kim, Jin-Dong
Gonzalez-Hernandez, Graciela
author_sort Weissenbacher, Davy
collection PubMed
description Despite a growing number of natural language processing shared-tasks dedicated to the use of Twitter data, there is currently no ad-hoc annotation tool for the purpose. During the 6th edition of Biomedical Linked Annotation Hackathon (BLAH), after a short review of 19 generic annotation tools, we adapted GATE and TextAE for annotating Twitter timelines. Although none of the tools reviewed allow the annotation of all information inherent of Twitter timelines, a few may be suitable provided the willingness by annotators to compromise on some functionality.
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spelling pubmed-73629422020-07-23 An empirical evaluation of electronic annotation tools for Twitter data Weissenbacher, Davy O'Connor, Karen Hiraki, Aiko T. Kim, Jin-Dong Gonzalez-Hernandez, Graciela Genomics Inform Opinion Despite a growing number of natural language processing shared-tasks dedicated to the use of Twitter data, there is currently no ad-hoc annotation tool for the purpose. During the 6th edition of Biomedical Linked Annotation Hackathon (BLAH), after a short review of 19 generic annotation tools, we adapted GATE and TextAE for annotating Twitter timelines. Although none of the tools reviewed allow the annotation of all information inherent of Twitter timelines, a few may be suitable provided the willingness by annotators to compromise on some functionality. Korea Genome Organization 2020-06-17 /pmc/articles/PMC7362942/ /pubmed/32634878 http://dx.doi.org/10.5808/GI.2020.18.2.e24 Text en (c) 2020, Korea Genome Organization (CC) This is an open-access article distributed under the terms of the Creative Commons Attribution license(https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Opinion
Weissenbacher, Davy
O'Connor, Karen
Hiraki, Aiko T.
Kim, Jin-Dong
Gonzalez-Hernandez, Graciela
An empirical evaluation of electronic annotation tools for Twitter data
title An empirical evaluation of electronic annotation tools for Twitter data
title_full An empirical evaluation of electronic annotation tools for Twitter data
title_fullStr An empirical evaluation of electronic annotation tools for Twitter data
title_full_unstemmed An empirical evaluation of electronic annotation tools for Twitter data
title_short An empirical evaluation of electronic annotation tools for Twitter data
title_sort empirical evaluation of electronic annotation tools for twitter data
topic Opinion
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7362942/
https://www.ncbi.nlm.nih.gov/pubmed/32634878
http://dx.doi.org/10.5808/GI.2020.18.2.e24
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