Explainability in Irony Detection

Autor: Pinar Karagoz, Adnan Harun Dogan, Ege Berk Buyukbas, Asli Umay Ozturk
Rok vydání: 2021
Předmět:
Zdroj: Big Data Analytics and Knowledge Discovery ISBN: 9783030865337
DaWaK
Popis: Irony detection is a text analysis problem aiming to detect ironic content. The methods in the literature are mostly for English text. In this paper, we focus on irony detection in Turkish and we analyze the explainability of neural models using Shapley Additive Explanations (SHAP) and Local Interpretable Model-Agnostic Explanations (LIME). The analysis is conducted on a set of annotated sample sentences.
Databáze: OpenAIRE