A Study of Big Data-Based Employees’ Public Opinion System Construction

Jin Li, Xiaobo Xu
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引用次数: 14

Abstract

With the rapid development of the Internet and big data, social self-media such as Weibo, WeChat, Tiktok, and QQ space has directly contributed to the speed and the channel of employees’ public opinions. The convergence and the impact of emotion are getting faster and faster. Timely and effective understanding and grasping the changes and development of employees’ public opinion has become an important topic. The development of big data technology makes it possible and necessary to construct an employees’ public opinion system. Based on big data and theories of public opinion generation and dissemination, this paper built a big data-based employees’ public opinion system and its main functions, including big data collection, data processing, data storage, data analysis, data visualization, and early warning of employees’ public opinion. Finally, we also defined the rich connotation of employees’ public opinion index.
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基于大数据的员工舆情系统建设研究
随着互联网和大数据的快速发展,微博、微信、抖音、QQ空间等社交自媒体直接促进了员工舆论的传播速度和渠道。情感的趋同和影响越来越快。及时有效地了解和把握员工舆论的变化和发展,已成为一个重要的课题。大数据技术的发展使得构建员工舆情系统成为可能和必要。本文基于大数据和舆情生成与传播理论,构建了基于大数据的员工舆情系统及其主要功能,包括大数据采集、数据处理、数据存储、数据分析、数据可视化、员工舆情预警等。最后,对员工民意指数的丰富内涵进行了界定。
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来源期刊
CiteScore
17.00
自引率
16.70%
发文量
31
期刊介绍: The Journal of Industrial Integration and Management: Innovation & Entrepreneurship concentrates on the technological innovation and entrepreneurship within the ongoing transition toward industrial integration and informatization. This journal strives to offer insights into challenges, issues, and solutions associated with industrial integration and informatization, providing an interdisciplinary platform for researchers, practitioners, and policymakers to engage in discussions from the perspectives of innovation and entrepreneurship. Welcoming contributions, The Journal of Industrial Integration and Management: Innovation & Entrepreneurship seeks papers addressing innovation and entrepreneurship in the context of industrial integration and informatization. The journal embraces empirical research, case study methods, and techniques derived from mathematical sciences, computer science, manufacturing engineering, and industrial integration-centric engineering management.
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