A Fast and Accurate Method for Bilingual Opinion Lexicon Extraction

The explosion of multilingual opinion data has made essential the need for automatic tools to analyze and understand people's opinions in multilingual reviews. In cross-language opinion mining, bilingual opinion lexicon plays a central role. Most of the bilingual lexicon extraction methods are based on EM algorithm. However, these methods are faced with two major problems: high complexity and unsatisfying precision. In this paper, we propose a novel approach to extract bilingual opinion lexicon using collocation alignment, where a collocation is a combination of a feature word and an opinion word. There are tight association between feature words and opinion words, which can be helpful to reduce the computation space and alignment errors. Experimental results demonstrate that our solution is effective and competitive.