基于HNC理论的文本情感倾向性分析

Analyzing Textual Sentiment Based on HNC Theory

【目的】构建一种更加科学、准确的评论文本情感倾向性分析方法,解决网络新词难于计算的问题。【方法】利用概念层次网络(HNC)理论的符号对偶性计算情感值,根据建立的规则为新词确定符号,利用符号重用降低工作量,实现对新词的处理。【结果】通过对已有成果的分析和改进,最终得到一套较为完善的情感倾向性分析方法,并使用真实数据进行实验,验证了该方法的可行性,同时也发现了待改进之处。【局限】目前仅能对网络短文本进行分析,且新词的加入需采用人工标注的方式。【结论】本文方法可行有效,为文本情感分析提供了新思路。

[Objective] This sutdy proposes a new method to conduct sentiment analysis with comment texts, aiming to deal with the issues facing new online terms. [Methods] Based on the Hierarchical Network of Concepts（HNC） theory, we defined symbols for the new words, which could be processed more efficiently. [Results] The proposed method analyzed the sentiment of the textual message effectively. [Limitations] Our method could only process short texts, while we still need to manually create symbols for the new words. [Conclusions] We proposed an effective way to conduct sentiment analysis.