Prediction of Development Prospect of Electric Vehicles in China by Using Natural Language Processing

S. Zheng, Qianhui Jin, Longtao Wang, Haoran Zhang
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引用次数: 1

Abstract

It is believed that people's comments on a certain product may affect its sales condition. In this paper, we propose a method to predict the sales of electric vehicles by analyzing people's comments on social media. We scrap user comments from a Chinese social media “Weibo” and try to predict the electric vehicle sales in China by using Natural Language Processing (NLP). Sentiment score, number of comments and likes, and keyword existence are treated as input indicators. We test linear regression, random forest, and gradient boosting algorithm during the experiment. The result shows that the model which using gradient boosting algorithm to predict the market share of electric vehicles has the best performance.
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基于自然语言处理的中国电动汽车发展前景预测
人们对某种产品的评价可能会影响其销售状况。在本文中,我们提出了一种通过分析人们在社交媒体上的评论来预测电动汽车销量的方法。我们从中国社交媒体“微博”上提取用户评论,并尝试使用自然语言处理(NLP)来预测中国的电动汽车销量。情感评分、评论和点赞数、关键词存在度作为输入指标。我们在实验中测试了线性回归、随机森林和梯度增强算法。结果表明,采用梯度增强算法预测电动汽车市场份额的模型具有最好的性能。
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