TY - JOUR T1 - Study on Prediction Model of Personal Economic Level Based on Text Analysis Using Chinese Classified Lexicon AU - Yahui Chen, Zhan Wen, Xia Zu, Yuwen Pan and Wenzao Li JO - Journal of Information and Computing Science VL - 1 SP - 044 EP - 051 PY - 2024 DA - 2024/01 SN - 14 DO - http://doi.org/ UR - https://global-sci.org/intro/article_detail/jics/22431.html KW - text analysis, logistic regression, personal economic level, prediction model. AB - Obtaining economic situation of the group is a key step in understanding the socio-economic situation like the division of the rich and the poor. But the traditional way to obtain economic situation of the group is based on the survey data of professionals and mathematical models. Such methods are time- consuming and too dependent on professionals. Therefore, the use of data mining techniques to judge and predict the economic situation of the group came into being. Such methods are efficient that can overcome the shortcomings of the traditional methods. In this paper, we started by acquiring the individual's economic level and finally established a personal economic level prediction model. Through large-scale access to the individual's economic level, the economic level of the group can be obtained. We analyzed the Chinese text data published on the network by Individuals with logistic regression model to explore whether the above text data can reflect a person's economic status. The experimental results indicate that personal created textual data is able to forecast the individual's economic level accurately and certain categories of vocabulary have an impact on the individual's economic level.

Yahui Chen, Zhan Wen, Xia Zu, Yuwen Pan and Wenzao Li. (2024). Study on Prediction Model of Personal Economic Level Based on Text Analysis Using Chinese Classified Lexicon. Journal of Information and Computing Science. 14 (1). 044-051. doi: