3 research outputs found
Social inertia in collaboration networks
This work is a study of the properties of collaboration networks employing
the formalism of weighted graphs to represent their one-mode projection. The
weight of the edges is directly the number of times that a partnership has been
repeated. This representation allows us to define the concept of "social
inertia" that measures the tendency of authors to keep on collaborating with
previous partners. We use a collection of empirical datasets to analyze several
aspects of the social inertia: 1) its probability distribution, 2) its
correlation with other properties, and 3) the correlations of the inertia
between neighbors in the network. We also contrast these empirical results with
the predictions of a recently proposed theoretical model for the growth of
collaboration networks.Comment: 7 pages, 5 figure
Correlations in Bipartite Collaboration Networks
Collaboration networks are studied as an example of growing bipartite
networks. These have been previously observed to have structure such as
positive correlations between nearest-neighbour degrees. However, a detailed
understanding of the origin of this phenomenon and the growth dynamics is
lacking. Both of these are analyzed empirically and simulated using various
models. A new one is presented, incorporating empirically necessary ingredients
such as bipartiteness and sublinear preferential attachment. This, and a
recently proposed model of team assembly both agree roughly with some empirical
observations and fail in several others.Comment: 13 pages, 17 figures, 2 table, submitted to JSTAT; manuscript
reorganized, figures and a table adde