微博的兴起与传播使得短文本情感分类成为目前的热门研究领域。通过对中文微博语料的情感倾向性分析进行研究,提出了一种新的情感分类方法。首先构建了两级情感词典,并对不同级别情感词作不同增强;然后在情感特征方面使用N-Gram方法,尽量获取有限长度博文中的未登录情感词和情感信息。经实验验证与传统方式相比较,该方法的准确率和召回率都有所提高,在COAE2014微博情感倾向性评测任务中也取得了较好的成绩。
The rise and spread of Micro-blog make sentiment classification on short texts become a hot area.A new method was proposed for Micro-blog sentiment classification.First of all,this method will create an emotional dictiona-ry with two-levels,and the words for different levels will get different enhancement;then in order to get features, N-gram method was used,which found new emotional words and emotional information from a short text.The experi-ment results show this approach has improved precision and recall rate compared to the traditional ways.This algorithm also did a very good job in COAE 2014.