Year: 2018
Type: conference-paper
Abstract: This paper describes our system created for the SemEval-2018 Task 3: Irony detection in English tweets.Our strongly constrained system uses only the provided training data without any additional external resources.Our system is based on Maximum Entropy classifier and various features using parse tree, POS tags, and morphological features.Even without additional lexicons and word embeddings we achieved fourth place in Subtask A and seventh in Subtask B in terms of accuracy.
DOI: 10.18653/v1/s18-1084
Author: Tomáš Hercig
Institution: University of West Bohemia in Pilsen
Language: English
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
Open Access status: hybrid
OpenAlex ID: W2806117226