一种基于图的情感基准词选择方法

Graph-Based Selection Method for Basic Sentimental Lexicons

作为文本情感分析的前提和基础,词语的情感极性判别显得尤为重要。现有利用情感基准词进行词语的情感倾向研究中,情感基准词的选择多数基于研究者的人工判别或词语的使用频率。以上方式存在着随机性和主观性的缺陷,并且难以保证对词典中语义关系的全面覆盖。本文提出以候选基准词为顶点,两词间的知网相似度作为边的权重设定参数来构建情感词的无向图。将图中结点的中介性值作为基准词的选择依据,从而保证所选基准词的可靠性。实验证明,通过该方法选取出来的基准词在词的情感倾向分类中具有较高的准确率。

As the premise and basis of text sentimental analysis, the emotion polarity discrimination of lexicons is particularly important. Existing methods of select basic sentimental lexicons in the study of semantic tendency are mostly based on artificial discrimination and lexicons frequency. Those ways suffer the defects of randomness and subjectivity. And it is difficult to ensure the full coverage of the semantic relations in the dictionary. In the paper, we present a method that treats the candidate basic sentimental lexicons as the vertex and the HowNet acquaintance as edge weight to build sentimental lexicons undirect- ed graph. The betweeness-centrality value of nodes in the graph is used as the reference of basic lexicons selecting. Thus we can ensure the reliability of the selected basic lexicons. Experiments show our method has a high accuracy in the classification of emotional tendencies.