An ACO inspired weighting approach for the spectral partitioning of co-authorship networks

Spectral partitioning is a well known method in the area of graph and matrix analysis. Several approaches based on spectral partitioning and spectral clustering were used to detect structures in real world networks and databases. In this paper, we use the spectral partitioning to detect communities in a co-authorship network. The partitioning depends heavily on the weighting of the underlying network. We use an intuitive weighting scheme based on the ant colony optimization and show the communities found by spectral partitioning when using the ACO inspired weighting and when using trivial weighting based on the number of interactions between the authors.