At this year iKNOW’11 conference we did a publication on „Semantically driven Social Data Aggregation Interfaces for Research 2.0“ and explained our research efforts on Semantic Social Media by developing a browser for finding out similar person of interest.
First the presentation:
We propose a framework to address an important issue in thecontext of the ongoing adoption of the “Web 2.0” in science and research, often referred to as “Science 2.0” or “Research 2.0”. Agrowing number of people are linked via acquaintances and onlinesocial networks such as Twitter allows indirect access to a hugeamount of ideas. These ideas are contained in a massive humaninformation flow. That users of these networks producerelevant data is being shown in many studies. The problem however lies in discovering and verifying such a streamof unstructured data items. Another related problem is locating anexpert that could provide an answer to a very specific researchquestion. We are using semantic technologies (RDF, SPARQL3) ,common vocabularies (SIOC, FOAF, SWRC) and Linked Data(DBpedia, GeoNames, CoLinDa) to extract and minethe data about scientific events out of context of microblogs. Hereby we are identifying persons and organization related tothem based on entities of time, place and topic. The framework provides an API that allows quick access to the information that isanalyzed by our system. As a proof-of-concept we explain, implement and evaluate such a researcher profiling use case. It involves the development of a framework that focuses on the proposition of researches based on topics and conferences theyhave in common. This framework provides an API that allow quick access to the analyzed information. A demonstrationapplication: “Researcher Affinity Browser” shows how the APIsupports developers to build rich internet applications for Research 2.0. This application also introduces the concept“affinity” that exposes the implicit proximity between entities andusers based on the content users produced. The usability of ademonstration application and the usefulness of the framework itself are investigated with an explicit evaluation questionnaire.This user feedback led to important conclusions about successfulachievements and opportunities to further improve this effort.
Reference: De Vocht, L.; Selver, S.; Ebner, M.; Mühlburger, H. (2011) Semantically driven Social Data AggregationInterfaces for Research 2.0. – in: 11th International Conference on Knowledge Management and Knowledge Technologies (2011), S. 43:1 -43:10, International Conference on Knowledge Management (iKNow), ACM New York