Genomics Inform.  2020 Jun;18(2):e24. 10.5808/GI.2020.18.2.e24.

An empirical evaluation of electronic annotation tools for Twitter data

Affiliations
  • 1Department of Biostatistics, Epidemiology and Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
  • 2Database Center for Life Science, Research Organization of Information and Systems, Kashiwa, Chiba 277-0871, Japan

Abstract

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 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.

Keyword

annotation tool; natural language processing; social media mining
Full Text Links
  • GNI
Actions
Cited
CITED
export Copy
Close
Share
  • Twitter
  • Facebook
Similar articles
Copyright © 2021 by Korean Association of Medical Journal Editors. All rights reserved.     E-mail: koreamed@kamje.or.kr