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A computational framework for social-media-based business analytics and knowledge creation: empirical studies of CyTraSS
Enterprise Information Systems ( IF 4.4 ) Pub Date : 2020-10-27 , DOI: 10.1080/17517575.2020.1827299
Wingyan Chung 1, 2 , Elizabeth Mustaine 3 , Daniel Zeng 4, 5
Affiliation  

ABSTRACT

Social media (SM) platforms greatly facilitate business information sharing, customer relationship building, and client emotion expression. However, managing knowledge acquired from SM messages is challenged by limited human cognitive capability. This paper describes a computational framework for developing intelligent SM-based business analytics and visualization. The research developed a proof-of-concept system named CyTraSS to support intelligent analyses and visualization of 2,318,691 messages posted by 740,070 users who discuss trafficking topics on Twitter. The results demonstrate theoretical insights and practical usability of the framework, enhance understanding of knowledge creation with SM technology, and provide novel findings for business managers and policy makers.



中文翻译:

基于社交媒体的业务分析和知识创造的计算框架:CyTraSS 的实证研究

摘要

社交媒体 (SM) 平台极大地促进了业务信息共享、客户关系建立和客户情感表达。然而,管理从 SM 消息中获取的知识受到人类认知能力有限的挑战。本文描述了一种用于开发基于智能 SM 的业务分析和可视化的计算框架。该研究开发了一个名为 CyTraSS 的概念验证系统,以支持对 740,070 名在 Twitter 上讨论贩运主题的用户发布的 2,318,691 条消息进行智能分析和可视化。结果证明了该框架的理论见解和实际可用性,增强了对使用 SM 技术创造知识的理解,并为业务经理和政策制定者提供了新的发现。

更新日期:2020-10-27
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