Semantic Analytics on Social Networks: Experiences in Addressing the Problem of Conflict of Interest Detection
Authors: Boanerges Aleman-Meza, Meenakshi Nagarajan, Cartic Ramakrishnan, Li Ding, Pranam Kolari, Amit P. Sheth, Ismailcem Budak Arpinar, Anupam Joshi, Tim Finin
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.
Publication venue: 15th International World Wide Web Conference (WWW2006)
Notes:
- Nomitated for Best Paper Award
- Acceptance Rate: 11%
Citation: 15th International World Wide Web Conference,
Edinburgh, Scotland, May 23-26, 2006, pages 407-416
http://doi.acm.org/10.1145/1135777.1135838
Citation count: 2 (via Google Scholar)
Cited by:
Search Engines for Semantic Web Knowledge (XTech2006),
Spinning Multiple Social Networks for SemanticWeb (AAAI2006);
mentioned in various blogs due to Pentagon sets its sights on social networking websites (NewScientist Magazine);
picked up by slashdot: Detecting Conflict-Of-Interest on the Semantic Web
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See also:
- WWW2006 Details on this paper
- Ebiquity Lab Details on this paper
- Connotea's Bookmark on this paper
- Live Demo of Conflict of Interest Detection
Keywords: Semantic Web, Social Networks, Conflict of Interest, Peer Review Process, Semantic Analytics, Entity Disambiguation, Data Fusion, Semantic Associations, Ontologies, RDF