Enabling Knowledge Broker Analysis through Actor Clusters in Organizational Structures in Enterprise Social Media

Mia Leppälä, Jukka Huhtamäki
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Abstract

Knowledge brokers serve as facilitators of knowledge sharing. The extant literature calls for nuanced analyses of different organizational structures as the spaces knowledge brokers operate in. Our interest lies in formal, semiformal, and informal organizational network structures and in how knowledge brokers are positioned in them. In this paper, we outline a collaborative analysis method, with researchers from different disciplines working together in data sprints. The benefit of this process is that it enables analyzing large organizational networks with deep insights. Amplifying social network analysis with field knowledge offers a deeper understanding of the connections in the network. This paper describes the analysis process and proposes interdisciplinary data processing techniques. We applied the proposed method using an extensive empirical data set that includes intraorganizational social media interactions between employees in a global organization. Our analysis transforms enterprise social media data into a network model that describes an organization ’s social structure.
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基于企业社交媒体组织结构行动者集群的知识经纪人分析
知识经纪人是知识共享的推动者。现有的文献要求对不同的组织结构进行细致入微的分析,因为知识经纪人所处的空间。我们的兴趣在于正式、半正式和非正式的组织网络结构,以及知识经纪人如何在其中定位。在本文中,我们概述了一种协作分析方法,来自不同学科的研究人员在数据冲刺中一起工作。这个过程的好处是,它可以用深刻的见解来分析大型组织网络。用领域知识放大社会网络分析,可以更深入地理解网络中的联系。本文描述了分析过程,并提出了跨学科的数据处理技术。我们使用广泛的经验数据集应用了所提出的方法,其中包括全球组织中员工之间的组织内社交媒体互动。我们的分析将企业社会媒体数据转换为描述组织社会结构的网络模型。
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