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%.