With growing reluctance to store and disseminate sensitive data throughout a supply chain network, there is a need to understand sentiment of big data and ways of control to achieve greater economic viability in the service-oriented supply chain which reflect a greater focus on knowledge sharing from traditional supply chains. Social network data were collected after referencing a focal corporate media (CM) document. This study provides causal inference by first conducting a CM document search and then a social network post web scrape of postings that reference the CM document while controlling for time and other demographic variables. This study finds salience of the big data topic positively impacts stakeholder sentiment but not when future applications are discussed.

由于越来越不愿意在整个供应链网络中存储和传播敏感数据，因此有必要了解大数据的情感和控制方式，以在面向服务的供应链中实现更大的经济可行性，这反映出人们越来越重视来自以下方面的知识共享：传统供应链。社交网络数据是在参考主要公司媒体（CM）文档后收集的。这项研究通过首先进行CM文档搜索，然后在控制时间和其他人口统计变量的同时，在引用CM文档的社交网络中发布帖子的网络摘要来提供因果推理。这项研究发现，大数据主题的显着性会对利益相关者的情绪产生积极影响，但在讨论未来的应用程序时却没有。