Please use this identifier to cite or link to this item: https://dl.eusset.eu/handle/20.500.12015/3673
Title: Discovering Social Networks from Event Logs
Authors: van der Aalst, Wil M. P.
Reijers, Hajo A.
Song, Minseok
Keywords: business process management;data mining;Petri nets;process mining;social network analysis;workflow management
Issue Date: 2005
Publisher: Springer
metadata.dc.relation.ispartof: Computer Supported Cooperative Work (CSCW): Vol. 14, No. 6
metadata.mci.reference.pages: 549-593
Series/Report no.: Computer Supported Cooperative Work (CSCW)
Abstract: Process mining techniques allow for the discovery of knowledge based on so-called “event logs”, i.e., a log recording the execution of activities in some business process. Many information systems provide such logs, e.g., most WFM, ERP, CRM, SCM, and B2B systems record transactions in a systematic way. Process mining techniques typically focus on performance and control-flow issues. However, event logs typically also log the performer , e.g., the person initiating or completing some activity. This paper focuses on mining social networks using this information. For example, it is possible to build a social network based on the hand-over of work from one performer to the next. By combining concepts from workflow management and social network analysis, it is possible to discover and analyze social networks. This paper defines metrics, presents a tool, and applies these to a real event log within the setting of a large Dutch organization.
metadata.dc.identifier.doi: 10.1007/s10606-005-9005-9
URI: http://dx.doi.org/10.1007/s10606-005-9005-9
https://dl.eusset.eu/handle/20.500.12015/3673
ISSN: 1573-7551
Appears in Collections:JCSCW Vol. 14 (2005)

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