ICCS '08 Proceedings of the 16th international conference on Conceptual Structures: Knowledge Visualization and Reasoning
Analysis of a Real Online Social Network Using Semantic Web Frameworks
ISWC '09 Proceedings of the 8th International Semantic Web Conference
The KGRAM Abstract Machine for Knowledge Graph Querying
WI-IAT '10 Proceedings of the 2010 IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology - Volume 01
Ontologies are us: a unified model of social networks and semantics
ISWC'05 Proceedings of the 4th international conference on The Semantic Web
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Building on top of our results on semantic social network analysis, we present a community detection algorithm, SemTagP, that takes benefits of the semantic data that were captured while structuring the RDF graphs of social networks. SemTagP not only offers to detect but also to label communities by exploiting (in addition to the structure of the social graph) the tags used by people during the social tagging process as well as the semantic relations inferred between tags. Doing so, we are able to refine the partitioning of the social graph with semantic processing and to label the activity of detected communities. We tested and evaluated this algorithm on the social network built from Ph.D. theses funded by ADEME, the French Environment and Energy Management Agency. We showed how this approach allows us to detect and label communities of interest and control the precision of the labels.