基于图排序的词汇情感消歧研究

Word Emotion Disambiguation Based on Graph Ranking

词汇情感消歧是文本情感倾向性分析的关键技术之一。该文在分析比较了词汇情感消歧和词义消歧异同后,从情感分析角度出发,提出了基于图排序的词汇情感消歧方法。该方法通过自动获取和人工校正相结合的方式获得多情感词汇,然后根据语义关系构建词义关系图,进而在词义关系图上迭代计算直至收敛,最后选择多情感词汇的词义中权值最大的词义作为结果输出,从而实现情感消歧。该文分别在新浪微博语料库和情感语料库上验证了该方法的有效性。

Word emotion disambiguation is vital to sentiment analysis. After discussing the differences between word emotion disambiguation and word sense disambiguation, we select the multi emotional word automatically as well as manually. From the aspect of sentiment analysis, we propose a word emotion disambiguation method based on graph ranking which builds directed meaning graphs according to semantic relations, and iteratively seleetes the most weighted sense of the given word as the right output. Results from MicroBlog corpus and emotional corpus, prove our method is superior than the eithor the method based on part of speech and emotional frequencies or the method based on Bayesian model.