Year: 2018
Type: conference-paper
Abstract: In this paper we describe our participation in the SemEval-2018 task 3 Shared Task on Irony Detection.We have approached the task with our low dimensionality representation method (LDR), which exploits low dimensional features extracted from text on the basis of the occurrence probability of the words depending on each class.Our intuition is that words in ironic texts have different probability of occurrence than in non-ironic ones.Our approach obtained acceptable results in both subtasks A and B. We have performed an error analysis that shows the difference on correct and incorrect classified tweets.
DOI: 10.18653/v1/s18-1086
Authors: Bilal Ghanem, Francisco Rangel, Paolo Rosso
Institution: Universitat Politècnica de València
Language: English
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
Open Access status: hybrid
OpenAlex ID: W2807604073