Abstract

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.

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call

Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.