A Framework Concept for Profiling Researchers on Twitter using the Web of Data
Based upon findings and results from our recent research (De Vocht et al., 2011) we propose a generic framework concept for researcher profiling with appliance to the areas of ”Science 2.0” and ”Research 2.0”. Intensive growth of users in social networks, such as Twitter generated a vast amount of information. It has been shown in many previous works that social networks users produce valuable content for profiling and recommendations (Reinhardt et al., 2009; Java et al., 2007; De Vocht et al., 2011). Our research focuses on identifying and locating experts for specific research area or topic. In our approach we apply semantic technologies like (RDFb, SPARQLc), common vocabularies (SIOCd, FOAFe, MOATf, Tag Ontologyg) and Linked Datah (GeoNamesi, COLINDAj) (Berners-Lee, 2006; Bizer et al., 2012) .