Sentiment classification of Chinese cosmetic reviews based on integration of collocations and concepts
| DOI | https://doi.org/10.1108/EL-04-2019-0093 |
| Pages | 155-169 |
| Date | 25 November 2019 |
| Published date | 25 November 2019 |
| Author | Chihli Hung,You-Xin Cao |
| Subject Matter | Information & knowledge management,Information & communications technology,Internet |
Sentiment classification
of Chinese cosmetic reviews
based on integration of
collocations and concepts
Chihli Hung and You-Xin Cao
Department of Information Management, Chung Yuan Christian University,
Taoyuan, Taiwan
Abstract
Purpose –This paper aims to propose a novel approach which integrates collocations and doma inconcepts f or
Chinese cosmetic word of mouth (WOM) sentiment classification. Most sentiment analysis works by collecting
sentiment scores from each unigram or bigram. However, not every unigram or bigram in a WOM document
contains sentiments. Chinese collocations consist of the main sentiments of WOM. This paper reduces the
complexity of the document dimensionality and makes an improvement for sentiment classification.
Design/methodology/approach –This paper builds two contextual lexicons for feature words and
sentiment words, respectively. Based on these contextual lexicons, this paper uses the techniques of
associated rules and mutual information to build possible Chinese collocation sets. This paper applies
preference vector modellingas the vector representation approach to catch the relationship betweenChinese
collocationsand their associated concepts.
Findings –This paper compares the proposed preference vector models with benchmarks, using three
classification techniques (i.e. support vector machine, J48 decision tree and multilayer perceptron). According to
the experimental results, the proposed models outperform all benchmarks evaluated by the criterion of accuracy.
Originality/value –This paper focuses on Chinese collocationsand proposes a novel research approach
for sentiment classification. The Chinese collocations used in this paper are adaptable to the content and
domains. Finally,this paper integrates collocations with the preferencevector modelling approach, which not
only achieves a bettersentiment classification performance for Chinese WOM documentsbut also avoids the
curse of dimensionality.
Keywords Sentiment analysis, Word of mouth, Chinese collocation, Context-aware lexicon,
Preference vector modelling
Paper type Research paper
Introduction
This paper proposes a novel sentiment analysis approach which uses Chinese collocations
and concepts forcosmetic word of mouth sentiment classification. Wordof mouth (WOM) is
a means of communication between users who exchange their subjective experiences or
feelings about a product, a service, a brand, a job, an activity and so on based on a non-
commercial purpose (Arndt, 1967).With the expansion of social media on the internet,WOM
is diffused more rapidly, broadly, widely and without anygeographic limitation. Consumers
have become accustomed to searching online for some pieces of relevant WOM before
This work was supported in part by the Ministry of Science and Technology of Taiwan under Grant
MOST 106-2410-H-033-014-MY2 and 104-2410-H-033-039-MY2.
Sentiment
classification
155
Received15 April 2019
Revised4 September 2019
Accepted8 October 2019
TheElectronic Library
Vol.38 No. 1, 2020
pp. 155-169
© Emerald Publishing Limited
0264-0473
DOI 10.1108/EL-04-2019-0093
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