Web-Based Annotation Tool for Instant Messaging Conversations

PLHÁK, Jaromír, Michaela LEBEDÍKOVÁ, Michal TKACZYK and David ŠMAHEL. Web-Based Annotation Tool for Instant Messaging Conversations. Online. In A. Horák, P. Rychlý, A. Rambousek (eds.). Recent Advances in Slavonic Natural Language Processing, RASLAN 2023. Brno: Tribun EU, Brno, 2023, p. 3-10. ISBN 978-80-263-1793-7.

Basic information

• Original name: Web-Based Annotation Tool for Instant Messaging Conversations
• Authors: PLHÁK, Jaromír (203 Czech Republic, guarantor, belonging to the institution), Michaela LEBEDÍKOVÁ (203 Czech Republic, belonging to the institution), Michal TKACZYK (616 Poland, belonging to the institution) and David ŠMAHEL (203 Czech Republic, belonging to the institution).
• Edition: Brno, Recent Advances in Slavonic Natural Language Processing, RASLAN 2023, p. 3-10, 8 pp. 2023.
• Publisher: Tribun EU, Brno

Other information

• Original language: English
• Type of outcome: Proceedings paper
• Field of Study: 10201 Computer sciences, information science, bioinformatics
• Country of publisher: Czech Republic
• Confidentiality degree: is not subject to a state or trade secret
• Publication form: electronic version available online
• WWW: URL
• RIV identification code: RIV/00216224:14330/23:00134339
• Organization unit: Faculty of Informatics
• ISBN: 978-80-263-1793-7
• ISSN: 2336-4289
• Keywords in English: Text annotation tool; online risky behavior; social support
• Tags: International impact, Reviewed

Abstract

This paper presents a customized web-based annotation tool that allows users to annotate utterances in data from instant messaging applications. Efficient annotations are provided by a well-arranged user interface, operating using key-pressing and integration of an interactive annotation manual. Moreover, the interface for supervisors allows them to determine which utterances belong to the gold standard. We also provide information on two accomplished annotation tasks: annotating online risk phenomena with sparse occurrence (0.85% to 1.98%) and annotating social support that can be used to generate efficient detection models.

Links

• GX19-27828X, research and development project: Name: Pohled do budoucnosti: Porozumění vlivu technologií na “well-being” adolescentů (Acronym: FUTURE)

Investor: Czech Science Foundation