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Semantic Analytics on Social Networks: Experiences in Addressing the Problem of Conflict of Interest Detection

  • Boanerges Aleman-Meza, LSDIS Lab, Dept. of Computer Science. University of Georgia, USA
  • Meenakshi Nagarajan, LSDIS Lab, Dept. of Computer Science. University of Georgia, USA
  • Cartic Ramakrishnan, LSDIS Lab, Dept. of Computer Science. University of Georgia, USA
  • Li Ding, University of Maryland Baltimore County, USA
  • Pranam Kolari, Department of Computer Science and Electrical Engineering University of Maryland, USA
  • Amit Sheth, LSDIS Lab Department of Computer Science University of Georgia, USA
  • I. Budak Arpinar, LSDIS Lab, Dept. of Computer Science. University of Georgia, USA
  • Anupam Joshi, Department of Computer Science and Electrical Engineering University of Maryland, USA
  • Tim Finin, Department of Computer Science and Electrical Engineering University of Maryland, USA
Nominated for Best Paper Award

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Track: Semantic Web

In this paper, we describe a Semantic Web application that detects Conflict of Interest (COI) relationships among potential reviewers and authors of scientific papers. This application discovers various 'semantic associations' between the reviewers and authors in a populated ontology to determine a degree of Conflict of Interest. This ontology was created by integrating entities and relationships from two social networks, namely "knows," from a FOAF (Friend-of-a-Friend) social network and "co-author," from the underlying co-authorship network of the DBLP bibliography. We describe our experiences developing this application in the context of a class of Semantic Web applications, which have important research and engineering challenges in common. In addition, we present an evaluation of our approach for real-life COI detection.

Citation

Aleman-Meza, B., Nagarajan, M., Ramakrishnan, C., Ding, L., Kolari, P., Sheth, A. P., Arpinar, I. B., Joshi, A., and Finin, T. 2006. Semantic analytics on social networks: experiences in addressing the problem of conflict of interest detection. In Proceedings of the 15th International Conference on World Wide Web (Edinburgh, Scotland, May 23 - 26, 2006). WWW '06. ACM Press, New York, NY, 407-416.
DOI= http://doi.acm.org/10.1145/1135777.1135838

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