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%.
Author: | Bianka Trevisan, Melanie Neunerdt, Tim Hemig, Eva-Maria Jakobs, Rudolf Mathar |
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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): | ![]() |