Volltext-Downloads (blau) und Frontdoor-Views (grau)

Detecting Irony Patterns in Multi-level Annotated Web Comments

  • Ironic speech act detection is indispensable for automatic opinion mining. This paper presents a pattern-based approach for the detection of ironic speech acts in German Web comments. The approach is based on a multilevel annotation model. Based on a gold standard corpus with labeled ironic sentences, multilevel patterns are deter- mined according to statistical and linguis- tic analysis. The extracted patterns serve to detect ironic speech acts in a Web com- ment test corpus. Automatic detection and inter-annotator results achieved by human annotators show that the detection of ironic sentences is a challenging task. However, we show that it is possible to automatically detect ironic sentences with relatively high precision up to 63%.

Download full text files

Export metadata

Additional Services

Share in Twitter    Search Google Scholar    frontdoor_oas
Metadaten
Author:Bianka Trevisan, Melanie Neunerdt, Tim Hemig, Eva-Maria Jakobs, Rudolf Mathar
URN:https://nbn-resolving.org/urn:nbn:de:gbv:hil2-opus-3120
Parent Title (English):Workshop proceedings of the 12th edition of the KONVENS conference
Document Type:Conference Proceeding
Language:English
Date of Publication (online):2014/11/25
Release Date:2014/11/25
Tag:NER; Named entity recognition
GND Keyword:Computerlinguistik; Computerunterstützte Kommunikation
First Page:34
Last Page:41
PPN:Link zum Katalog
Institutes:Fachbereich III / Informationswissenschaft und Sprachtechnologie
DDC classes:400 Sprache / 400 Sprache, Linguistik
Collections:KONVENS 2014 / Workshop Proceedings of the 12th KONVENS 2014
Licence (German):License LogoCreative Commons - Namensnennung 3.0