Article: Community Cube: a semantic framework for analysing social network data Journal: International Journal of Metadata, Semantics and Ontologies (IJMSO) 2015 Vol.10 No.3 pp.155 - 169 Abstract: Social network research has focused mainly on the inference of social influence, building of user communities and prediction analysis. However, very little work has been carried out to investigate and document how online analytical processing (OLAP) tools can interactively analyse social networks according to different perspectives and with multiple granularities. In this paper we study the use of data warehousing and OLAP technologies with such new multidimensional social network by proposing Community Cube architecture. Going beyond traditional OLAP operations, our architecture proposes a new method that combines data mining and OLAP tools to navigate through the user hierarchy. Besides traditional OLAP queries, our approach introduces a new class of queries, which we named 'NetCuboid'. These queries take into account the attributes associated with networks entities, the user-generated content, and the topological structure of the networks. Experimental results showcase the effectiveness of our approach for decision-making based on social network data. Inderscience Publishers - linking academia, business and industry through research

Title: Community Cube: a semantic framework for analysing social network data

Authors: Lilia Hannachi; Nadjia Benblidia; Omar Boussaid; Fadila Bentayeb

Addresses: LRDSI Laboratory, University of Blida, Saad Dahlab AV. Soumaa BP 270 BLIDA, Algeria ' LRDSI Laboratory, University of Blida, Saad Dahlab AV. Soumaa BP 270 BLIDA, Algeria ' ERIC Laboratory, University of Lyon 2, 5 AV. P. Mendes-France 69676 Bron Cedex Lyon, France ' ERIC Laboratory, University of Lyon 2, 5 AV. P. Mendes-France 69676 Bron Cedex Lyon, France

Abstract: Social network research has focused mainly on the inference of social influence, building of user communities and prediction analysis. However, very little work has been carried out to investigate and document how online analytical processing (OLAP) tools can interactively analyse social networks according to different perspectives and with multiple granularities. In this paper we study the use of data warehousing and OLAP technologies with such new multidimensional social network by proposing Community Cube architecture. Going beyond traditional OLAP operations, our architecture proposes a new method that combines data mining and OLAP tools to navigate through the user hierarchy. Besides traditional OLAP queries, our approach introduces a new class of queries, which we named 'NetCuboid'. These queries take into account the attributes associated with networks entities, the user-generated content, and the topological structure of the networks. Experimental results showcase the effectiveness of our approach for decision-making based on social network data.

Keywords: data warehousing; online analytical processing; OLAP; social network analysis; SNA; community extraction; semantics; data mining; decision making.

DOI: 10.1504/IJMSO.2015.073876

International Journal of Metadata, Semantics and Ontologies, 2015 Vol.10 No.3, pp.155 - 169

Received: 29 Dec 2014
Accepted: 16 Jun 2015
Published online: 27 Dec 2015 *

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Title: Community Cube: a semantic framework for analysing social network data

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