Research Article
Analysis on User Satisfaction on Helping Farmers Live based on Text Mining and Structural Equation Modeling
@INPROCEEDINGS{10.4108/eai.17-6-2022.2322728, author={Xinyi Li and Zuxin Meng and Zhuoyi Li and Yuhui Li}, title={Analysis on User Satisfaction on Helping Farmers Live based on Text Mining and Structural Equation Modeling}, proceedings={Proceedings of the International Conference on Information Economy, Data Modeling and Cloud Computing, ICIDC 2022, 17-19 June 2022, Qingdao, China}, publisher={EAI}, proceedings_a={ICIDC}, year={2022}, month={10}, keywords={helping farmers live; agricultural products; text-mining; k-means clustering; structural equation modeling}, doi={10.4108/eai.17-6-2022.2322728} }- Xinyi Li
Zuxin Meng
Zhuoyi Li
Yuhui Li
Year: 2022
Analysis on User Satisfaction on Helping Farmers Live based on Text Mining and Structural Equation Modeling
ICIDC
EAI
DOI: 10.4108/eai.17-6-2022.2322728
Abstract
Live video streaming has become a popular means of merchandising, more and more farmers are trying to use commerce live streaming to sell their agricultural products. This paper uses text mining technology to design a questionnaire, identifies important and potential user groups through K-means clustering, and uses structural equation modeling to verify the structural relationship between the impact of live streaming, anchor, product and service on the satisfaction of farming live streaming users. The results show that: the satisfaction of users on Helping Farmers Live stay at a basic level, there exist enough space to improve it; their loyalty on Helping Farmers Live is still low, and the frequency of repurchase behavior is not high; the easy-to-use groups for Helping Farmers Live are young, middle-income and rural consumers.