利用人工神经网络分析电子产品评论中的情感极性

Bambang Pilu Hartato, Tri Astuti, Irnawati Pratika, R. Wahyudi, Irfan Santiko, Andi Riyanto
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引用次数: 1

摘要

智能系统目前已被证明在人类生活的各个方面提供更多的好处。其中一种方法是情绪分析(SA)方法。情景分析是一种数学方法,它允许机器分析陈述或文档的观点极性。一般来说,情景分析是用来观察公众对一个问题的意见倾向。SA还可以用于电子商务,根据客户给出的评论来分析客户对产品的陈述趋势。因此,SA将帮助电子商务企业主了解对所提供产品的接受程度。在本文中,我们试图评估人工神经网络(ANN)算法在电子产品评价中的应用。在本研究中,采用1个输入层,1个包含10个神经元的隐藏层,1个包含2个神经元的输出层来设计神经网络。我们的实验结果表明,ANN在对已经进行过的电子产品评审进行SA时,具有相当高的准确度和精密度,分别为70.80%和71.07%。因此,ANN非常有可能应用于智能系统,这些系统的任务是帮助电子商务企业所有者根据客户提供的反馈进行SA。
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Artificial Neural Network Utilization for Analyzing Sentiment Polarity in Electronics Product Reviews
Intelligent systems currently have been proven to provide more benefits on various aspects of human life. One of them is sentiment analysis (SA) approach. SA is a mathematical approach that allows machines to analyze the opinion polarity of the statements or documents. Generally, SA is utilized to observe the tendency of public opinion on an issue. SA can also be used on e-commerce to analyze the trend of customer statements toward a product based on the reviews given by them. Thus, SA will help e-commerce business owners to know the level of acceptance toward offered products. In this paper, we try to evaluate the artificial neural network (ANN) algorithm in conducting a SA of electronic products reviews. In this study, the ANN was designed using 1 input layer, 1 hidden layer consisting of 10 neurons, and 1 output layer consisting of 2 neurons. Our experimental results showed that the ANN had a fairly high accuracy and precision while conducting SA toward electronic products reviews that have been carried out, i.e. 70.80% and 71.07% respectively. Hence, ANN is very possible to be applied to intelligent systems that are tasked to assist e-commerce business owners in conducting SA toward feedback provided by the customers.
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