Enabling Knowledge Broker Analysis through Actor Clusters in Organizational Structures in Enterprise Social Media
Files
Date
2022-01-04
Authors
Contributor
Advisor
Department
Instructor
Depositor
Speaker
Researcher
Consultant
Interviewer
Narrator
Transcriber
Annotator
Journal Title
Journal ISSN
Volume Title
Publisher
Volume
Number/Issue
Starting Page
Ending Page
Alternative Title
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.
Description
Keywords
Distributed Collaboration and Telework in Organizations and Networks, cluster detection, data-sprint, knowledge broker, social network analysis
Citation
Extent
9 pages
Format
Geographic Location
Time Period
Related To
Proceedings of the 55th Hawaii International Conference on System Sciences
Related To (URI)
Table of Contents
Rights
Attribution-NonCommercial-NoDerivatives 4.0 International
Rights Holder
Local Contexts
Email libraryada-l@lists.hawaii.edu if you need this content in ADA-compliant format.