用反向传播法进行情绪分析以识别舆论

I. A. Wiguna, P. Sugiartawan, I. Sudipa, I. P. Y. Pratama
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引用次数: 0

摘要

通过对旅游企业所属的数字平台进行情绪分析,收集负面情绪,提高旅游企业所属公司的服务质量,提高旅游行为体的服务质量。印尼酒店业的增长每年都在快速增长。旅游业作为酒店业的一部分,也没有逃脱正面和负面情绪的影响。一种进行准确情感分析的方法是反向传播神经网络。通过对神经网络的测试结果表明,采用一层隐含层,第一层隐含10个神经元时,准确率最高。学习率为0.000002,其中准确率为71.630%。更多的年代并不能保证更好的准确性。基于已经完成的研究结果,建议进一步研究人员分析综述数据集的处理方法,使其得到更干净的数据集,并有望提高准确性。
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Sentiment Analysis Using Backpropagation Method to Recognize the Public Opinion
Improve the service quality of tourism actors by conducting sentiment analysis on digital platforms owned by tourism businesses and collecting negative sentiments to improve the quality of services from companies owned by tourism businesses. The growth of the hospitality industry in Indonesia is experiencing rapid growth every year. The tourism industry, part of the hospitality industry, also does not escape the influence of positive and negative sentiments. One method to perform accurate sentiment analysis is Backpropagation Neural Network. Based on the results of tests on the neural network, the best accuracy is obtained when using one hidden layer with the first layer of 10 neurons. The learning rate is 0.000002, where the accuracy is 71.630%. More epochs do not guarantee better accuracy. Based on the results of the research that has been done, suggestions for further researchers are to analyze the review dataset processing method so that it gets a cleaner dataset and is expected to improve better accuracy.
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