Sarcasm Detection using Sentiment and Semantic Features

Prateek Nagwanshi, C. E. Veni Madhavan

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 Harvard Style

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


in Bibtex Style

@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},
}


in EndNote Style

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