Mining Social Networks: Uncovering Interaction Patterns in Business Processes

  • Wil M. P. van der Aalst
  • Minseok Song
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3080)


Increasingly information systems log historic information in a systematic way. Workflow management systems, but also ERP, CRM, SCM, and B2B systems often provide a so-called “event log”, i.e., a log recording the execution of activities. Unfortunately, the information in these event logs is rarely used to analyze the underlying processes. Process mining aims at improving this by providing techniques and tools for discovering process, control, data, organizational, and social structures from event logs. This paper focuses on the mining social networks. This is possible because event logs typically record information about the users executing the activities recorded in the log. To do this we combine concepts from workflow management and social network analysis. This paper introduces the approach, defines metrics, and presents a tool to mine social networks from event logs.


Social Network Process Mining Social Network Analysis Geodesic Distance Process Instance 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2004

Authors and Affiliations

  • Wil M. P. van der Aalst
    • 1
  • Minseok Song
    • 1
    • 2
  1. 1.Department of Technology ManagementEindhoven University of TechnologyEindhovenThe Netherlands
  2. 2.Dept. of Industrial EngineeringPohang University of Science and TechnologyNam-gu, PohangSouth Korea

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