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Knowledge work is mainly based on task- or topic-related communication among employees. Much of their time is allocated for searching and maintaining helpful contacts for specific business questions. By that, large yet invisible relationship networks develop. Understanding and utilizing such communities leverages the efficiency of knowledge transfer and collaboration in a company.
Based on detailed foundations of Knowledge Management and Communities of Practice, this book shows that organizations are essentially knowledge networks of communication. Taking this perspective, a detailed procedure for ITsupported network analysis of knowledge communities based on their communication is introduced together with the required Social Network Intelligence Software. Using a transparent visual network model and a comprehensive network measurement system, the approach integrates methods from Dynamic Social Network Analysis, Information Visualization, and Text Mining
to identify, monitor and analyze networks. Four practical cases demonstrate how this helps to identify important information bottle necks, important people, clusters, emerging topics, or lifecycles in knowledge communities. The book targets community moderators, corporate managers with a focus on groups and knowledge work, and researchers or students of network analysis.
Über den Autor / die Autorin
Dr. Matthias Trier arbeitet am Institut für Wirtschaftsinformatik an der Technischen Universität Berlin. Er leitet dort die Forschungsgruppe IKM mit den Schwerpunkten Wissensmanagement und E-Learning Produktion. Ein gegenwärtiger Fokus ist die Identifikation, Visualisierung und Analyse netzwerkorientierter virtueller Gemeinschaften zur Verbesserung kollaborativer wissensintensiver Unternehmensbereiche. Herr Dr. Trier ist Autor internationaler Veröffentlichungen, Mitorganisator der weltweit tätigen virtuellen Universität VGU und führt zahlreiche Unternehmensprojekte und Lehre in den Bereichen Geschäftsprozessoptimierung und Wissensmanagement durch.
