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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Bibliographic Details
Published in:	Genomics & informatics Vol. 18; no. 2; p. e24
Main Authors:	Weissenbacher, Davy, O'Connor, Karen, Hiraki, Aiko T., Kim, Jin-Dong, Gonzalez-Hernandez, Graciela
Format:	Journal Article
Language:	English
Published:	Korea Genome Organization 01-06-2020
Subjects:	annotation tool natural language processing Opinion social media mining
Online Access:	Get full text
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Summary:	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.
Bibliography:	ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 23
ISSN:	2234-0742 1598-866X 2234-0742
DOI:	10.5808/GI.2020.18.2.e24