Our contribution to this year WEBIST Conference about “A Framework Concept for Profiling Researchers on Twitter using the Web of Data” is now online as draft version available.
Abstract:
Based upon findings and results from our recent research (De Vocht et al., 2011) we propose a generic frame- work 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 (RDF, SPARQL), common vocabularies (SIOC, FOAF, MOAT, Tag Ontology) and Linked Datah (GeoNames, COLINDA) (Berners-Lee, 2006; Bizer et al., 2012).
A Framework Concept for Profiling Researchers on Twitter using the Web of Data by Martin
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Reference: Softic, S., Ebner, M., De Vocht, L., Mannens, E., Van de Walle, R.: A Framework Concept for Profiling Researchers on Twitter using the Web of Data. Proceedings of the 9th International Conference on Web Information Systems and Technologies (WEBIST) 2013, SciTePress 2013, Karl-Heinz Krempels, Alexander Stocker (Eds.), pp.447-452, ISBN 978-989-8565-54-9, Aachen, Germany, 8 – 10 May, 2013.