Considering the diversities and ambiguities of opinion expressions in Chinese online product reviews,
normal sentiment analysis technologies have exposed their inadequateness in both classification accuracy and identifying
effectiveness. We propose a novel approach which can easily identify product features and corresponding
opinions by building a domain-specific affective ontology and thus mapping comment sentences to the objects defined
in the affective ontology. Ontology is created automatically by processing the online reviews; both product
features and affective words are presented as nodes which are connected to each other by their semantic relationship.
Furthermore, in order to increase the accuracy, we introduce a dynamic polarity detection technique
for affective words whose sentimental tendencies are dependent on particular contexts. The experimental results
clearly demonstrate the performance improvement of our approach compared with others in real world online
product reviews for classification tests.
LIU Li-zhen (刘丽珍), LIU Hao (刘昊), WANG Han-shi* (王函石),SONG Wei (宋巍), ZHAO Xin-lei (赵新蕾)
. Generating Domain-Specific Affective Ontology from Chinese Reviews for Sentiment Analysis[J]. Journal of Shanghai Jiaotong University(Science), 2015
, 20(1)
: 32
-37
.
DOI: 10.1007/s12204-015-1584-0
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