AuthorRank+FOAF: Ranking for Co-Authorship Networks on the Web

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.