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Authors: Johannes Liegl ; Stefan Gindl ; Arno Scharl and Alexander Hubmann-Haidvogel

Affiliation: MODUL University Vienna, Austria

Keyword(s): Sentiment Detection, Natural Language Processing, Latent Semantic Analysis, Pointwise Mutual Information

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

Abstract: This paper investigates approaches to improve the accuracy of automated sentiment detection in textual knowledge repositories. Many high-throughput sentiment detection algorithms rely on sentiment dictionaries containing terms classified as either positive or negative. To obtain accurate and comprehensive sentiment dictionaries, we merge existing resources into a single dictionary and extend this dictionary by means of semisupervised learning algorithms such as Pointwise Mutual Information - Information Retrieval (PMI-IR) and Latent Semantic Analysis (LSA). The resulting extended dictionary is then evaluated on various datasets from different domains, which were annotated on both the document and sentence level.

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Paper citation in several formats:
Liegl, J., Gindl, S., Scharl, A., Hubmann-Haidvogel and A. (2010). DICTIONARY EXTENSION FOR IMPROVING AUTOMATED SENTIMENT DETECTION. In Proceedings of the International Conference on Knowledge Discovery and Information Retrieval (IC3K 2010) - KDIR; ISBN 978-989-8425-28-7; ISSN 2184-3228, SciTePress, pages 404-407. DOI: 10.5220/0003070304040407

@conference{kdir10,
author={Johannes Liegl and Stefan Gindl and Arno Scharl and Alexander Hubmann{-}Haidvogel},
title={DICTIONARY EXTENSION FOR IMPROVING AUTOMATED SENTIMENT DETECTION},
booktitle={Proceedings of the International Conference on Knowledge Discovery and Information Retrieval (IC3K 2010) - KDIR},
year={2010},
pages={404-407},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0003070304040407},
isbn={978-989-8425-28-7},
issn={2184-3228},
}

TY - CONF

JO - Proceedings of the International Conference on Knowledge Discovery and Information Retrieval (IC3K 2010) - KDIR
TI - DICTIONARY EXTENSION FOR IMPROVING AUTOMATED SENTIMENT DETECTION
SN - 978-989-8425-28-7
IS - 2184-3228
AU - Liegl, J.
AU - Gindl, S.
AU - Scharl, A.
AU - Hubmann-Haidvogel, A.
PY - 2010
SP - 404
EP - 407
DO - 10.5220/0003070304040407
PB - SciTePress

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