A study on graduation diversion of college students based on LDA model

Abstract

The significance of college students' graduation diversion is to effectively adjust the talent structure and improve the efficiency of social resource allocation. In this paper, firstly, through text mining, the diversion direction is divided into three parts, namely,taking Postgraduate Entrance Examination,get postgraduate recommendation and employment, and python is used to crawl the relevant comments on microblogging about graduation diversion. Then, the crawled text is applied the jieba library to split words. Then, the LDA topic model was applied to model the participle results, and a total of 11, 21 and 23 numbers were obtained for employment, postgraduate recommendation and Postgraduate Entrance Examination respectively. From the results of the model, it can be seen that college students choose to take Postgraduate Entrance Examination in the current graduation stream, and the number of getting postgraduate recommendation and employment is small. This suggests that the government should intervene in the employment environment, and it also suggests that college students should multitask simultaneously.