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This paper focuses on the automatic extraction of domain-specific sentimentword (DSSW), which is a fundamental subtask of sentiment analysis. Mostprevious work utilizes manual patterns for this task. However, the performanceof those methods highly relies on the labelled patterns or selected seeds. Inorder to overcome the above problem, this paper presents an automatic frameworkto detect large-scale domain-specific patterns for DSSW extraction. To thisend, sentiment seeds are extracted from massive dataset of user comments.Subsequently, these sentiment seeds are expanded by synonyms using abootstrapping mechanism. Simultaneously, a synonymy graph is built and thegraph propagation algorithm is applied on the built synonymy graph. Afterwards,syntactic and sequential relations between target words and high-rankedsentiment words are extracted automatically to construct large-scale patterns,which are further used to extracte DSSWs. The experimental results in threedomains reveal the effectiveness of our method.

Domain-Specific Sentiment Word Extraction by Seed Expansion and Pattern Generation