Emotional Research on Mobile Phone E-Commerce Reviews on LSTM Model

Emotional analysis has been omnipresent. Grabbing adequate information from online shopping evaluation and analyzing it can provide a basis to choose for businesses or consumers. Taking “Jingdong Mall” mobile e-commerce review as an example, the authors of this paper use web crawler technology to obtain sufficient data of 12 products under 7 mobile phone brands in the sales ranking. The authors then use Python’s Jieba library to segment the reviews and gensim module to train word2vec word vector model and classify the mobile e-commerce reviews by constructing LSTM neural network model. It is concluded that the consumers’ views that there exists some advantages and disadvantages of “Apple” and “Huawei” mobile phones.