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Authors: David Pereira Coutinho 1 and Mário A. T. Figueiredo 2

Affiliations: 1 Instituto Superior de Engenharia de Lisboa and Instituto de Telecomunicações, Portugal ; 2 Instituto Superior Técnico and Instituto de Telecomunicações, Portugal

ISBN: 978-989-8565-41-9

Keyword(s): Sentiment Analysis, Binary Categorization, Ziv-Merhav Method, Cross Parsing, Lempel-Ziv Algorithm.

Related Ontology Subjects/Areas/Topics: Applications ; Artificial Intelligence ; Data Engineering ; Information Retrieval ; Knowledge Engineering and Ontology Development ; Knowledge-Based Systems ; Natural Language Processing ; Ontologies and the Semantic Web ; Pattern Recognition ; Software Engineering ; Symbolic Systems

Abstract: Most approaches to text sentiment analysis rely on human generated lexicon-based feature selection methods, supervised vector-based learning methods, and other solutions that seek to capture sentiment information. Most of these methods, in order to yield acceptable accuracy, require a complex preprocessing stage and careful feature engineering. This paper introduces a coding-theoretic-based sentiment analysis method that dispenses with any text preprocessing or explicit feature engineering, but still achieves state-of-the-art accuracy. By applying the Ziv-Merhav method to estimate the relative entropy (Kullback-Leibler divergence) and the cross parsing length from pairs of sequences of text symbols, we get information theoretic measures that make very few assumptions about the models which are assumed to have generated the sequences. Using these measures, we follow a dissimilarity space approach, on which we apply a standard support vector machine classifier. Experimental evaluation o f the proposed approach on a text sentiment analysis problem (more specifically, movie reviews sentiment polarity classification) reveals that it outperforms the previous state-of-the-art, despite being much simpler than the competing methods. (More)

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Paper citation in several formats:
Pereira Coutinho, D. and A. T. Figueiredo, M. (2013). An Information Theoretic Approach to Text Sentiment Analysis.In Proceedings of the 2nd International Conference on Pattern Recognition Applications and Methods - Volume 1: ICPRAM, ISBN 978-989-8565-41-9, pages 577-580. DOI: 10.5220/0004269005770580

@conference{icpram13,
author={David Pereira Coutinho. and Mário A. T. Figueiredo.},
title={An Information Theoretic Approach to Text Sentiment Analysis},
booktitle={Proceedings of the 2nd International Conference on Pattern Recognition Applications and Methods - Volume 1: ICPRAM,},
year={2013},
pages={577-580},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0004269005770580},
isbn={978-989-8565-41-9},
}

TY - CONF

JO - Proceedings of the 2nd International Conference on Pattern Recognition Applications and Methods - Volume 1: ICPRAM,
TI - An Information Theoretic Approach to Text Sentiment Analysis
SN - 978-989-8565-41-9
AU - Pereira Coutinho, D.
AU - A. T. Figueiredo, M.
PY - 2013
SP - 577
EP - 580
DO - 10.5220/0004269005770580

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