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| The Quantitative Algorithm of Sentiment Divergence Based on Web User Reviews |
| Xu Jian, Wu Siyang |
| School of Information Management, Sun Yat-sen University, Guangzhou 510006 |
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Abstract 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.
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Received: 23 March 2019
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