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NEUOM: Identifying Opinionated Sentences in Chinese and English Text

This paper introduces our NEUOM system which participates in the opinionated sentence detection task, one of evaluation tasks in Multilingual Opinion Analysis Task (MOAT) of NTCIR-7. NEUOM system adopts a sentiment lexicon-based(SLB) approach to identifying opinionated sentences in a Chinese text and English text. For English task, a machine learning algorithm, naive Bayesian classification model, is also tried with the use of the English training corpora, such as MPQA and NTCIR-6 data set. Experimental results show that in the English task SLB method achieved better F1 performance than Naive Bayesian model.