Analysis of SIGMOD's co-authorship graph
ACM SIGMOD Record
Optimized Index Structures for Querying RDF from the Web
LA-WEB '05 Proceedings of the Third Latin American Web Congress
Analysis of a Real Online Social Network Using Semantic Web Frameworks
ISWC '09 Proceedings of the 8th International Semantic Web Conference
Co-authorship networks in the digital library research community
Information Processing and Management: an International Journal - Special issue: Infometrics
A Uniform Semantic Web Framework for Co-authorship Networks
DASC '11 Proceedings of the 2011 IEEE Ninth International Conference on Dependable, Autonomic and Secure Computing
Discovering influential authors in heterogeneous academic networks by a co-ranking method
Proceedings of the 22nd ACM international conference on Conference on information & knowledge management
| Hi-index | 0.00 |
The FOAF ontology has become a core model for describing social data of people and their links on the Web, and the people ranking is growing in popularity since search engines are considering the author's reputation of a Web page when generating search results. FOAF alone is yet insufficient to model social networks for ranking people on the Web. We concentrate here in co-authorship networks as a special case of social networks, and propose a model which extends FOAF with Page Rank and Author Rank metrics, both implemented in Semantic Web Rule Language (SWRL), for gauging the reputation of authors. Preliminary results are demonstrated, showcasing also the huge potential of this ranking approach for adopting it on social networks in general, and by search engines in particular where our future work will focus.