Business Stakeholder Analyzer: An Automatic Classification Approach to Facilitating Collaborative Commerce on the Web
2014 47th Hawaii International Conference on System Sciences (2005)
Big Island, Hawaii
Jan. 3, 2005 to Jan. 6, 2005
Wingyan Chung , The University of Texas at El Paso
As the Web is used increasingly to share and disseminate information, business analysts and managers are challenged to understand stakeholder relationships. Traditional stakeholder analysis approaches fail to accommodate the rapid Web growth while existing business intelligence tools lack analysis capability. This paper proposes an automatic classification approach to business stakeholder analysis on the Web. Based on the approach, we developed a system called Business Stakeholder Analyzer to perform automatic classification of stakeholder types. Experimental results showed that, compared with humans, the system achieved better within-class accuracies in widespread stakeholder types such as "partner/sponsor/supplier" and "media/reviewer." It was more efficient than human classification. The encouraging findings suggest a promising future of our approach to facilitating knowledge sharing in collaborative commerce.
stakeholder analysis, Web page classification, business intelligence, feature selection, neural network, Support Vector Machines
Wingyan Chung, "Business Stakeholder Analyzer: An Automatic Classification Approach to Facilitating Collaborative Commerce on the Web", 2014 47th Hawaii International Conference on System Sciences, vol. 01, no. , pp. 15c, 2005, doi:10.1109/HICSS.2005.134