With the development of Internet technology, more and more businesses begin to open up online sales channels, which is both an opportunity and a challenge. In order to stand out from the competitive sales environment, it is a very effective means to obtain and analyze the feedback information in the product review data. Businesses can improve and publicize products through the feedback information to improve sales. This paper implements a set of fast insight system based on emotion analysis and neural network. The system can configure the collection items through the visual interface, and then use the data collection module to collect data from the e-commerce platform to build a commodity comment corpus. At the same time, it also embeds two emotion analysis models to analyze the processed comment data. The two-layer emotion tendency model is responsible for coarse-grained emotion analysis of the comment data to obtain commodity word of mouth, The comment theme model is responsible for fine-grained emotional analysis of the comment data to get the comment theme of the commodity. The analysis results can help merchants get the improvement points and promotion points of the commodity.

Logesh Sridevi. Emotion Analysis of Shopping Software Reviews Based on Neural Network. International Journal of Neural Network (2021), Vol. 2, Issue 1: 44-51. https://doi.org/10.38007/NN.2021.020106.

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