An empirical evaluation of electronic annotation tools for Twitter data

Autor: Davy Weissenbacher, Karen O'Connor, Aiko T. Hiraki, Jin-Dong Kim, Graciela Gonzalez-Hernandez
Jazyk: angličtina
Rok vydání: 2020
Předmět:
Zdroj: Genomics & Informatics, Vol 18, Iss 2, p e24 (2020)
Druh dokumentu: article
ISSN: 2234-0742
DOI: 10.5808/GI.2020.18.2.e24
Popis: 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.
Databáze: Directory of Open Access Journals