@Article{JICS-14-044, author = {Yahui Chen, Zhan Wen, Xia Zu, Yuwen Pan and Wenzao Li}, title = {Study on Prediction Model of Personal Economic Level Based on Text Analysis Using Chinese Classified Lexicon}, journal = {Journal of Information and Computing Science}, year = {2019}, volume = {14}, number = {1}, pages = {044--051}, abstract = { 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. }, issn = {3080-180X}, doi = {https://doi.org/}, url = {http://global-sci.org/intro/article_detail/jics/22431.html} }