ROBUST: Risk and Opportunity management of huge-scale BUSiness communiTy cooperation

Online communities have emerged in all areas of society, and their use is now widespread in social, business, scientific and public service domains. They enable the community members to collaborate through shared ideas, knowledge and opinion. Thus, online communities generate major economic value to business and can form pivotal parts of corporate expertise management, corporate marketing, product support, customer relationship management, product innovation and targeted advertising. The objective of ROBUST is to analyze, manage and care for online communities, in order support their well being, to provide access to the created values and to exploit the knowledge and information contained within. This requires the development of metrics, models and algorithms in several fields. ROBUST addresses these requirements in the context of three key topics: Data mining in online communities: The analysis of online communities covers generated contents, structural aspects of social networks and interactions, as well as the behavior of individuals or groups. On one hand, this analysis serves risk and opportunity detection, management and response, based on pre-defined objectives for a given community. On the other hand, it serves the community members as it supports the users in having their needs and requirements satisfied. Community modeling and simulation: Community models can be used to analyze and measure the dynamics of the community itself. This allows managing, protecting and optimizing the health of online communities and spans the behavior of individuals and administrative activities. Based on such a model, an appropriate simulation framework can be used to predict the development of online communities in a given setting. This allows, in turn, taking administrative and corrective measures to ensure the well being of the community. Large scale data management: Cloud based data management and efficient algorithms ensure the scalability of the approaches to the data volume generated by online communities. This includes developing an efficient algebraic basis for querying and retrieving community data. All developments aim at a real time analysis of a community and the contents it generates. The scientific contributions in all of these fields are implemented as software packages and will be plugged into a common service oriented architecture. This integration is central to the project and provides a coherent software platform as backbone for the achievements of ROBUST. End user applications will be built on top of this framework. These use cases provide the practical grounding for the work done in ROBUST. Real world business requirements, data and scenarios are used to prove the scalability, flexibility and transferability of the results. Additionally, the use cases are an integral part of the exploitation strategy and promote the results of the project to the widest possible audience.


The project consortium includes 5 academic groups and 5 industrial partners. Academic partners are: University of Koblenz-Landau, Germany; National University of Ireland, Galway; University of Southampton, UK; TU Berlin, Germany; and Open University / Knowledge Media Institute, UK.. Industrial partners are: SAP Research, Germany; IBM Haifa Research Lab, Israel; Temis, France; Software Mind, Poland; and MeaningMine, Ireland.

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