Sentiment Classification for Hotel Booking Review Based on Sentence Dependency Structure and Sub-Opinion Analysis


IEICE TRANSACTIONS on Information and Systems   Vol.E101-D   No.4   pp.909-916
Publication Date: 2018/04/01
Publicized: 2018/01/19
Online ISSN: 1745-1361
DOI: 10.1587/transinf.2016IIP0038
Type of Manuscript: Special Section PAPER (Special Section on Intelligent Information and Communication Technology and its Applications to Creative Activity Support)
Category: Datamining Technologies
sentiment analysis,  sentence dependency parsing,  subtree opinions,  Vietnamese sentiment classification,  hotel review classification,  

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This paper presents a supervised method to classify a document at the sub-sentence level. Traditionally, sentiment analysis often classifies sentence polarity based on word features, syllable features, or N-gram features. A sentence, as a whole, may contain several phrases and words which carry their own specific sentiment. However, classifying a sentence based on phrases and words can sometimes be incoherent because they are ungrammatically formed. In order to overcome this problem, we need to arrange words and phrase in a dependency form to capture their semantic scope of sentiment. Thus, we transform a sentence into a dependency tree structure. A dependency tree is composed of subtrees, and each subtree allocates words and syllables in a grammatical order. Moreover, a sentence dependency tree structure can mitigate word sense ambiguity or solve the inherent polysemy of words by determining their word sense. In our experiment, we provide the details of the proposed subtree polarity classification for sub-opinion analysis. To conclude our discussion, we also elaborate on the effectiveness of the analysis result.