微博情感分析的情感词典构造及分析方法研究

摘要

In order to improve the accuracy of micro-blog sentiment analysis, semantic rules and sentiment dictionary in micro-blog sentiment analysis are studied.The constructing method of micro-blog sentiment dictionary in sentiment dictionary is improved on the basis of the traditional sentiment analysis based on sentiment dictionary.First of all, we construct the sentiment dictionary including the opensource sentiment dictionary, the net sentiment dictionary with the characteristics of the times, micro-blog sentiment dictionary based on position of emotional words on the basis of constructed dictionaries, and motional sentiment dictionary with obvious emotion tendency.Based on the completion of the construction of the lexicon, combined with the Chinese grammar rules, including the rule of relationship between sentences and rules of sentence patterns, the sentiment tendencies of Weibo sentences are calculated according to algorithm of relationship between sentences and sentence patterns.The micro-blog texts are divided into three categories:positive, negative and neutral section.In order to improve the classification accuracy, we propose to construct a modal dictionaries and make innovations in the modal weight calculation of the modal particles.At the same time, the construction method of the micro-blog sentiment dictionary is improved.Experiment shows that this method can improve the accuracy of the emotional analysis of micro-blog.%为了提高微博情感分析的准确性, 对微博情感分析中的语义规则和情感词典进行了研究.在传统基于情感词典的微博情感分析的基础上对情感词典中的微博情感词典的构造方法做了改进.首先构造情感词典, 主要包括开源情感词典、具有时代特征的网络情感词典、根据情感词的位置特点构造的微博情感词典、具有明显情感倾向的语气情感词典.在词典构造完成的基础上结合中文语法规则, 主要包括句间关系规则和句型关系规则, 根据句间和句型关系算法计算微博句子的情感倾向性, 将微博文本分为正向、负向和中性三个方面.为了提高微博分类的准确率, 提出构建语气词词典, 并且在语气词权重计算的方法上做出创新, 同时对微博情感词典的构造方法做出了改进.实验结果表明, 该方法能够提高微博情感分析的正确率.