基于在线评论的就业行业情报挖掘研究——以图书情报专业求职者为例  

Research on Employment Industry Intelligence Mining Based on Online Reviews: A Case Study on Job Applicants Majoring in Library and Information Science

作　　者：吕宏玉 杨建林[1] Lv Hongyu

机构地区：[1]南京大学信息管理学院,江苏南京210023

出　　处：《情报理论与实践》2020年第9期63-71,共9页Information Studies:Theory & Application

基　　金：国家社会科学基金重点项目“面向国家发展与安全决策的情报服务创新研究”的成果,项目编号:18ATQ003。

摘　　要：[目的/意义]择业难成为我国高校毕业生求职的新问题,数量庞大但碎片化的招聘信息对行业选择的指导作用有限。为保证做出正确的择业决策,求职者需要可以反映不同行业整体情况的情报。[方法/过程]文章提出一种基于在线评论的就业行业情报挖掘方法,以就职员工对企业的评论为数据源,挖掘员工对企业整体及7个具体维度的情感态度。在此基础上引用竞争情报的思想,分析得到用于支持专业人才决策的行业情况情报。[结果/结论]文章以图书情报专业求职者的行业选择为例展示方法的实际应用过程。该方法丰富了就业指导信息的来源,为求职者的就业决策提供具有对比性质的行业情况情报,能够引导专业人才认知不同行业,提高就业行业匹配度。[Purpose/significance]The difficulty of choosing a job has become a new problem for college graduates in China.A large number of fragmented recruitment information has limited guiding effects on industry selection.In order to make the right decision,job applicants need intelligence that reflects the overall situation of different industries.[Method/process]This paper proposes a method of mining employment industry intelligence based on online reviews.Taking the employees’reviews on enterprises as the data source,this paper explores the employees’overall attitude towards the enterprises they worked for and the attitudes towards seven specific dimensions.On this basis,industry situation intelligence to support the decision-making of job applicants in specific major is obtained by using the thought of competitive intelligence.[Result/conclusion]This paper takes the employment industry selection for job applicants majoring in Library and Information Science as an example to show the practical application process of the method.This method enriches the sources of career guidance information,provides comparative industry situation information for job applicants’career decision-making,guides job applicants of different majors to understand different industries,and improves the matching degree of employment industry.

关 键 词：员工评论 评论挖掘 竞争情报 专业人才 就业指导 行业情报 

分 类 号：G350[文化科学—情报学] F249.2[经济管理—劳动经济]