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arXiv · 1801.00254

A New Approach for Measuring Sentiment Orientation based on Multi-Dimensional Vector Space

Youngsam Kim·Hyopil Shin
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Abstract

This study implements a vector space model approach to measure the sentiment orientations of words. Two representative vectors for positive/negative polarity are constructed using high-dimensional vec-tor space in both an unsupervised and a semi-supervised manner. A sentiment ori-entation value per word is determined by taking the difference between the cosine distances against the two reference vec-tors. These two conditions (unsupervised and semi-supervised) are compared against an existing unsupervised method (Turney, 2002). As a result of our experi-ment, we demonstrate that this novel ap-proach significantly outperforms the pre-vious unsupervised approach and is more practical and data efficient as well.

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Youngsam Kim, Hyopil Shin. 2017-12-31. A New Approach for Measuring Sentiment Orientation based on Multi-Dimensional Vector Space. https://arxiv.org/abs/1801.00254

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