Study on Prediction Model of Personal Economic Level Based on Text Analysis Using Chinese Classified Lexicon

Abstract

Obtaining \u00a0economic \u00a0situation \u00a0of \u00a0the \u00a0group \u00a0is \u00a0a \u00a0key \u00a0step \u00a0in \u00a0understanding \u00a0the \u00a0socio-economic situation like the division of the rich and the poor. But the traditional way to obtain economic situation of the group \u00a0is \u00a0based \u00a0on \u00a0the \u00a0survey \u00a0data \u00a0of \u00a0professionals \u00a0and \u00a0mathematical \u00a0models. \u00a0Such \u00a0methods \u00a0are \u00a0time- consuming \u00a0and \u00a0too \u00a0dependent \u00a0on \u00a0professionals. \u00a0Therefore, \u00a0the \u00a0use \u00a0of \u00a0data \u00a0mining \u00a0techniques \u00a0to \u00a0judge \u00a0and 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 \u00a0published \u00a0on \u00a0the \u00a0network \u00a0by \u00a0Individuals \u00a0with \u00a0logistic \u00a0regression \u00a0model \u00a0to \u00a0explore \u00a0whether \u00a0the \u00a0above text \u00a0data \u00a0can \u00a0reflect \u00a0a \u00a0person's \u00a0economic \u00a0status. \u00a0The \u00a0experimental \u00a0results \u00a0indicate \u00a0that \u00a0personal \u00a0created 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.