UMBC ebiquity

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

Authors: Boanerges Aleman-Meza, Meenakshi Nagarajan, Cartic Ramakrishnan, Amit Sheth, Budak Arpinar, Li Ding, Pranam Kolari, Anupam Joshi, and Tim Finin

Book Title: Proceedings of the 15th International World Wide Web Conference,

Date: May 23, 2006

Abstract: 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.

Type: InProceedings

Publisher: ACM Press

Note: DOI= http://doi.acm.org/10.1145/1135777.1135838

Pages: 407-416

Tags: social networking, semantic web, foaf, rdf, trust, foaf

Google Scholar: _7TRAvS3l2EJ

Number of Google Scholar citations: 106 [show citations]

Number of downloads: 2876

 

Available for download as


size: 422791 bytes
 

Related Projects:

Past Project

 Semantic Discovery: Discovering Complex Relationships in Semantic Web.