Research Article
Evaluation of Word-of-Mouth Influence of Cross-Border E-commerce Products Based on Social Network Data Analysis
@INPROCEEDINGS{10.1007/978-3-031-50543-0_27, author={Weiwei Zhang and Yuanting Lu and Lingming Cao and Hui Li}, title={Evaluation of Word-of-Mouth Influence of Cross-Border E-commerce Products Based on Social Network Data Analysis}, proceedings={Advanced Hybrid Information Processing. 7th EAI International Conference, ADHIP 2023, Harbin, China, September 22-24, 2023, Proceedings, Part I}, proceedings_a={ADHIP}, year={2024}, month={3}, keywords={Social Network Data Analysis Cross-Border E-Commerce Product Reputation Effect Assessment Weight Calculation}, doi={10.1007/978-3-031-50543-0_27} }- Weiwei Zhang
Yuanting Lu
Lingming Cao
Hui Li
Year: 2024
Evaluation of Word-of-Mouth Influence of Cross-Border E-commerce Products Based on Social Network Data Analysis
ADHIP
Springer
DOI: 10.1007/978-3-031-50543-0_27
Abstract
To improve the performance of word-of-mouth impact assessment for cross-border e-commerce products, a method based on social network data analysis is proposed for evaluating the word-of-mouth impact of cross-border e-commerce products. Eliminate abnormal users on social networks and establish an evaluation index system for the reputation and influence of cross-border e-commerce products. Based on this system, the basic indicators for evaluating the word-of-mouth impact of cross-border e-commerce products are determined, and an indicator weight judgment matrix is constructed using Analytic Hierarchy Process to calculate the weight of the word-of-mouth impact evaluation indicators for cross-border e-commerce products. Based on the weight calculation results, a word-of-mouth impact evaluation algorithm for cross-border e-commerce products was designed to achieve the evaluation of word-of-mouth impact of cross-border e-commerce products. Case analysis demonstrates that this approach effectively evaluates the impact of word-of-mouth for cross-border e-commerce products with a 95% improvement in evaluation efficiency and reliability, boosting overall performance.
