Explainability in Irony Detection
Autor: | Pinar Karagoz, Adnan Harun Dogan, Ege Berk Buyukbas, Asli Umay Ozturk |
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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 |
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