网络用户评论的情感分歧度量化算法研究

The Quantitative Algorithm of Sentiment Divergence Based on Web User Reviews

从情感分歧角度出发,为网络用户评论情感分析提供新的研究方法和视角。借鉴已有的5种差异度、离散度计算公式,融入情感元素,应用于情感分歧度计算场景,分别得到基于情感值差、标准差、变异系数、信息熵、情感分布概率的5种情感分歧度量化算法,并且基于情感的正负值特点,提出基于正负情感比值的情感分歧度量化方法。在网络用户评论情感分析的基础上,利用这6种情感分歧度量化算法对用户评论进行情感分歧度量化,并对各种情感分歧度算法量化结果进行对比分析。实验结果表明,情感分歧度量化算法可实现对网络用户评论情感分歧度的量化;不同分歧度量化算法在适用性和区分度等方面的特点存在差异。

The main aim of this paper is to provide a new method and perspective to analyze the sentiment of web user reviews from the standpoint of sentiment divergence. Drawing on the five existing formulas for calculating the degrees of difference and dispersion, integrating the emotional elements and applying them to the scene for calculating sentiment divergence, five algorithms for measuring sentiment divergence based on emotional value difference, standard deviation, coefficient of variation, information entropy, and probability of emotional distribution are obtained. An algorithm for measuring sentiment divergence based on the frequency of positive and negative emotional values is proposed, which takes advantage of the fact that emotional values can be positive or negative. It is based on the sentiment analysis of text. This paper puts forward six quantitative algorithms of sentiment divergence to quantify the sentiment divergence of user reviews and analyzes the quantified results of sentiment divergence. The results show that the model can achieve the quantification of the sentiment divergence of web user reviews. However, there are differences in applicability and discrimination of different quantitative algorithms of sentiment divergence.