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

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Conference Proceeding

Abstract

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.

APA Citation

Aleman-Meza, B., Nagarajan, M., Ramakrishnan, C., Ding, L., Kolari, P., Sheth, A. P., Arpinar, I. B., Joshi, A., & Finin, T. (2006). Semantic Analytics on Social Networks: Experiences in Addressing the Problem of Conflict of Interest Detection. Proceedings of the 15th International conference on World Wide Web, 406-416.
https://corescholar.libraries.wright.edu/knoesis/34

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