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.
Date: May 23, 2006
Book Title: Proceedings of the 15th International World Wide Web Conference,
Type: InProceedings
Pages: 407-416
Publisher: ACM Press
Note: DOI= http://doi.acm.org/10.1145/1135777.1135838
Google scholar: _7TRAvS3l2EJ
Google citations: 54 citations
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Bibtex


@InProceedings{Semantic_Analytics_on_Social_Networks_Ex,
  author = "Boanerges Aleman-Meza and Meenakshi Nagarajan and Cartic Ramakrishnan and Amit Sheth and Budak Arpinar and Li Ding and Pranam Kolari and Anupam Joshi and Tim Finin",
  title = "{Semantic Analytics on Social Networks: Experiences in Addressing the Problem of Conflict of Interest Detection}",
  month = "May",
  year = "2006",
  note = "DOI= http://doi.acm.org/10.1145/1135777.1135838",
  pages = "407-416",
  booktitle = "Proceedings of the 15th International World Wide Web Conference,",
  publisher = "ACM Press",
}