Discovering social networks from event logs

被引:266
作者
Van Der Aalst W.M.P. [1 ]
Reijers H.A. [1 ]
Song M. [1 ,2 ]
机构
[1] Department of Technology Management, Eindhoven University of Technology, 513, NL-5600 MB, Eindhoven
[2] Department of Industrial Engineering, Pohang University of Science and Technology, Nam-gu, Pohang, 790-784
来源
Computer Supported Cooperative Work (CSCW) | 2005年 / 14卷 / 6期
关键词
Business process management; Data mining; Petri nets; Process mining; Social network analysis; Workflow management;
D O I
10.1007/s10606-005-9005-9
中图分类号
学科分类号
摘要
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. © Springer 2005.
引用
收藏
页码:549 / 593
页数:44
相关论文
共 51 条
[1]  
Agrawal R., Gunopulos D., Leymann F., Mining process models from workflow logs, Sixth International Conference on Extending Database Technology, pp. 469-483, (1998)
[2]  
Bavelas A., A mathematical model for group structures, Human Organization, 7, pp. 16-30, (1948)
[3]  
Begole J., Tang J., Smith R., Yankelovich N., Work rhythms: Analyzing visualizations of awareness histories of distributed groups, Proceedings of the 2002 ACM Conference on Computer Supported Cooperative Work, pp. 334-343, (2002)
[4]  
Bernard H., Killworth P., McCarty C., Shelley G., Robinson S., Comparing four different methods for measuring personal social networks, Social Networks, 12, pp. 179-216, (1990)
[5]  
Bonacich P., Power and centrality: A family of measures, American Journal of Sociology, 92, pp. 1170-1182, (1987)
[6]  
Burt R., Minor M., Applied Network Analysis: A Methodological Introduction, (1983)
[7]  
Clausen S.E., Applied Correspondence Analysis: An Introduction, (1998)
[8]  
Cook J., Wolf A., Discovering models of software processes from event-based data, ACM Transactions on Software Engineering and Methodology, 7, 3, pp. 215-249, (1998)
[9]  
Culotta A., Bekkerman R., McCallum A., Extracting social networks and contact information from email and the Web, Proceedings of the First Conference on Email and Anti-spam (CEAS), (2004)
[10]  
Ellis C., An Evaluation Framework for Collaborative Systems, (2000)