the 5th International Workshop on Business Applications of Social Network Analysis
co-located with 2014 IEEE International Conference on Data Mining (ICDM 2014)
December 14, 2014, Shenzhen, China.
Today organizations operate in a networked environment. Their success depends on several factors, one of them being their “network and business intelligence”, i.e., the ability to understand the relations (or lack of relations) between competitors, partners, suppliers, employees, and customers and exploit them towards specific business goals. Another one, is the ability to handle the enormous amount of data (volume), their continuous generation (velocity), different forms of data (variety) and the inherent data uncertainty (veracity), i.e, dealing with Big Data. Networks have always existed but the emergence of information and communication technologies has made them evident and traceable. Digitalized social and business relations may become the new data gold mine, feeding business strategies and decisions. Big data analytics have been traditionally performed on the entities in isolation. Incorporating the insights from the networks potentially provides a new perspective on issues such as customer behavior, community development, sharing of customer experiences, organizational change, knowledge management, stakeholder management, inter-organizational collaboration, scalable solutions, etc.
Recently, Social Network Analysis (SNA) has emerged also as one of the most innovative and successful fields of management research. With the digitalization of social relations and communications, management scholars are increasingly able to extract relational data from company websites, online organizational communications, news, and online databases. New research tools, like web surveys, web scraping tools, text analysis software, and data mining tools, facilitate the information extraction, organization, visualization, and interpretation. Also, the increasing computer power allows to process larger amounts of data (either relational or NOSQL data) using more sophisticated (and memory expensive distributed) methods. The more high volume company data are digitalized, collected, stored, organized, and integrated in enterprise data warehouses, the more opportunities for knowledge extraction and data mining and the more, SNA will be able support the identification and management of internal or external social networks for the creation of business value.
The aim of this workshop is to encourage multidisciplinary discussions related to novel ideas and application geared towards analyzing social network and media data. By bringing together researchers in the fields of SNA, data mining, big data and management studies, the workshop focuses on identifying the “grey” areas of collaboration among their respective disciplines:
- The role of big data analytics in identifying scalable methods for the extraction and organization of social relations for management research and business practice.
- The role of management research in guiding data mining efforts and SNA metrics development towards theoretically-grounded discoveries about social network emergence.
- The role of SNA in developing and applying metrics and tools for the mapping, evaluation, visualization, and design of social relations in organizations.