A New Approach to Detect Communities in Multi-weighted Co-authorship Networks

Co-authorship graphs related to publications (bibliographical production) are generally represented by undirected graphs, where each edge maintains a single value for publications produced by the authors. A variation of this type of graph is related to use of different weights associated with different types of publications. In this context, within the ?eld of scien to metrics, 'journal papers' or 'books' may have a higher priority than the 'conference papers', and the 'conference papers' might have higher priority than the 'extended abstract'. In this paper, we present a simple weight combination to detect communities in co-authorship networks, which allows simultaneous consideration of multiple types of collaborations. Our preliminary results show a good performance in the detection of communities considering real bibliographical production graphs.