基于员工在线评论的互联网企业工作满意度提升研究
首发时间:2021-03-15
摘要:对工作满意度影响因素的研究可以有效地解决互联网行业员工离职率居高不下的问题。鉴于在线评论已经成为一种重要的信息来源,文章选取在线平台--看准网上综合得分排名靠前的互联网企业为研究样本,挖掘员工评论文本,通过人工标注的评论语料在百度AI平台上训练出情感情绪分析模型计算各维度的情感得分。比照排名前三十的企业和排名后三十的企业之间的情感指数差异,探究互联网企业工作满意度的关键影响因素。结果显示互联网企业在提升工作满意度上应当关注管理水平、薪资、同事关系和发展前景。据此提出针对性的管理建议,这对于企业做出管理决策具有重要的参考意义。
关键词: 互联网企业 工作满意度 员工在线评论 情感倾向分析 情感指数
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Research on Improving Job Satisfaction of Internet Enterprises Based on Employees\' Online Reviews
Abstract:It can effectively solve the problem of high employee turnover rate in the Internet industry to do an exploration on the influencing factors of job satisfaction .Online reviews have become an important source of gaining information, so this paper selects the Internet companies with the highest comprehensive scores on Kanzhun as the research samples, excavates the text of employee comments, and builds a sentiment analysis model on Baidu AI platform using the manually marked comment corpus to calculate the emotional score of employees on each dimension. Compare the emotional index difference between the top 30 companies and the bottom 30 companies to explore the key influencing factors of job satisfaction for Internet companies. The results show that Internet companies should pay attention to management, salary, colleague relations and development prospects.This paper proposes targeted management recommendations based on this, which has important reference significance for enterprises to make important management decisions.
Keywords: Internet companies job satisfaction employee online reviews sentiment tendency analysis sentiment index
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基于员工在线评论的互联网企业工作满意度提升研究
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