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Authors: Asmaa Mountassir ; Houda Benbrahim and Ilham Berrada

Affiliation: ENSIAS and Mohamed 5 University, Morocco

ISBN: 978-989-8565-29-7

Keyword(s): Sentiment Analysis, Opinion Mining, Unbalanced Data Sets, Machine Learning, Text Classification, Natural Language Processing, Arabic Language.

Related Ontology Subjects/Areas/Topics: AI Programming ; Applications ; Applications and Case-studies ; Artificial Intelligence ; Knowledge Engineering and Ontology Development ; Knowledge Reengineering ; Knowledge Representation ; Knowledge-Based Systems ; Natural Language Processing ; Pattern Recognition ; Symbolic Systems

Abstract: Sentiment Analysis is a research area where the studies focus on processing and analysing the opinions available on the web. This paper deals with the problem of unbalanced data sets in supervised sentiment classification. We propose three different methods to under-sample the majority class documents, namely Remove Similar, Remove Farthest and Remove by Clustering. Our goal is to compare the effectiveness of the proposed methods with the common random under-sampling. We use for classification three standard classifiers: Naïve Bayes, Support Vector Machines and k-Nearest Neighbours. The experiments are carried out on two different Arabic data sets that we have built and labelled manually. We show that results obtained on the first data set, which is slightly skewed, are better than those obtained on the second one which is highly skewed. The results show also that we can rely on the proposed techniques and that they are typically competitive with random under-sampling.

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Paper citation in several formats:
Mountassir, A.; Benbrahim, H. and Berrada, I. (2012). Addressing the Problem of Unbalanced Data Sets in Sentiment Analysis.In Proceedings of the International Conference on Knowledge Discovery and Information Retrieval - Volume 1: KDIR, (IC3K 2012) ISBN 978-989-8565-29-7, pages 306-311. DOI: 10.5220/0004142603060311

@conference{kdir12,
author={Asmaa Mountassir. and Houda Benbrahim. and Ilham Berrada.},
title={Addressing the Problem of Unbalanced Data Sets in Sentiment Analysis},
booktitle={Proceedings of the International Conference on Knowledge Discovery and Information Retrieval - Volume 1: KDIR, (IC3K 2012)},
year={2012},
pages={306-311},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0004142603060311},
isbn={978-989-8565-29-7},
}

TY - CONF

JO - Proceedings of the International Conference on Knowledge Discovery and Information Retrieval - Volume 1: KDIR, (IC3K 2012)
TI - Addressing the Problem of Unbalanced Data Sets in Sentiment Analysis
SN - 978-989-8565-29-7
AU - Mountassir, A.
AU - Benbrahim, H.
AU - Berrada, I.
PY - 2012
SP - 306
EP - 311
DO - 10.5220/0004142603060311

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