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

In this paper, we describe a Semantic Web application that detects Conflict of Interest 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 is built by integrating entities and relationships from two social networks, namely 'knows' from a FOAF (Friendof- a-Friend) social network, and 'co-author' from the underlying co-authorship network of the DBLP bibliography. We describe our experiences on development of 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.