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Authors: Prateek Nagwanshi and C. E. Veni Madhavan

Affiliation: Indian Institute of Science, India

ISBN: 978-989-758-048-2

Keyword(s): Sarcasm Detection, Natural Language Processing, Opinion Mining, Computational Linguistics, Classification

Related Ontology Subjects/Areas/Topics: Artificial Intelligence ; Concept Mining ; Context Discovery ; Information Extraction ; Knowledge Discovery and Information Retrieval ; Knowledge-Based Systems ; Mining Text and Semi-Structured Data ; Symbolic Systems

Abstract: Sarcasm is a figure of speech used to express a strong opinion in a mild manner. It is often used to convey the opposite sense of what is expressed. Automatic recognition of sarcasm is a complex task. Sarcasm detection is of importance in effective opinion mining. Most sarcasm detectors use lexical and pragmatic features for this purpose. We incorporate statistical as well as linguistic features. Our approach considers the semantic and flipping of sentiment as main features. We use machine learning techniques for classification of sarcastic statements. We conduct experiments on different types of data sets, and compare our results with an existing approach in the literature. We also present human evaluation results. We propose to augment the present encouraging results by a new approach of integrating linguistic and cognitive aspects of text processing.

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Paper citation in several formats:
Nagwanshi, P. and Veni Madhavan, C. (2014). Sarcasm Detection using Sentiment and Semantic Features.In Proceedings of the International Conference on Knowledge Discovery and Information Retrieval - Volume 1: KDIR, (IC3K 2014) ISBN 978-989-758-048-2, pages 418-424. DOI: 10.5220/0005153504180424

@conference{kdir14,
author={Prateek Nagwanshi. and C. E. Veni Madhavan.},
title={Sarcasm Detection using Sentiment and Semantic Features},
booktitle={Proceedings of the International Conference on Knowledge Discovery and Information Retrieval - Volume 1: KDIR, (IC3K 2014)},
year={2014},
pages={418-424},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0005153504180424},
isbn={978-989-758-048-2},
}

TY - CONF

JO - Proceedings of the International Conference on Knowledge Discovery and Information Retrieval - Volume 1: KDIR, (IC3K 2014)
TI - Sarcasm Detection using Sentiment and Semantic Features
SN - 978-989-758-048-2
AU - Nagwanshi, P.
AU - Veni Madhavan, C.
PY - 2014
SP - 418
EP - 424
DO - 10.5220/0005153504180424

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