@twitter Mining #Microblogs Using #Semantic Technologies

Abstract

In this paper we report about our current and ongoi ng research efforts aiming at knowledge discovery, offline social data mining and social entity extraction based upon semantic technologies. Furthe r we are aiming to provide the scientific architecture paradigm for building s emantic applications that rely on social data. In this early stage our work focus es on data from Twitter 1 as currently most popular and fastest growing microblo gging platform. In the realm of our research we implemented applications l ike Grabeeter 2 for storing searching and caching the social data and STAT infr astructure that uses semantic standards like RDF (SIOC, FOAF), SPARQL and existing semantic services as Sinidice 3 and Linked Data silos as DBPedia 4 or GeoNames 5 as well. They represent parts of novel architecture paradigm for semantic social applications intended to be introduced here.