Table 1.

Literature survey.

Author/year	Techniques used	Methodology	Research findings
Yang et al. (2020)	Convolutional Neural Network (CNN) and attention-based Bidirectional Gated Recurrent Unit (BiGRU).	In reviews, the Sentiment Lexicon is utilized to enhance emotional characteristics.	This concept could help to keep track of text perception analysis.
Tseng et al. (2018)	Semantic analysis algorithm.	A novel forecasting model for the pricing of e-commerce products has been proposed.	Advised the creation of a new forecast model for the financial value of e-commerce items.
Zhang et al. (2020)	tf-idf algorithm.	A reverse dictionary for the same emotional phrases is constructed for different assessment objects with varied polarity.	The emotional categorization of e-commerce course exams improved as a result of the emotion lexicon produced in this study.
Yang et al. (2022)	Network evolutionand Sales distribution analysis.	The best-simulated sales distribution is quite close to the real thing, and it determines whether the network evolution technology is applicable.	The suggested method may be utilized to provide a standardized evaluation platform for communication research, which is an important part of procurement research.
Zhang and Zhong (2019)	Shortest path algorithm.	A large-scale E-commerce website reviews dataset is gathered to test the algorithms' accuracy and model feasibility.	Emotional similarity analysis, according to the findings, can be a beneficial method for determining user confidence in e-commerce systems.