Multilayer network decoding versatility and trust

Abstract

In the recent years, the multilayer networks have increasingly been realized\nas a more realistic framework to understand emergent physical phenomena in\ncomplex real world systems. We analyze a massive time-varying social data drawn\nfrom the largest film industry of the world under multilayer network framework.\nThe framework enables us to evaluate the versatility of actors, which turns out\nto be an intrinsic property of lead actors. Versatility in dimers suggests that\nworking with different types of nodes are more beneficial than with similar\nones. However, the triangles yield a different relation between type of\nco-actor and the success of lead nodes indicating the importance of higher\norder motifs in understanding the properties of the underlying system.\nFurthermore, despite the degree-degree correlations of entire networks being\nneutral, multilayering picks up different values of correlation indicating\npositive connotations like trust, in the recent years. Analysis of weak ties of\nthe industry uncovers nodes from lower degree regime being important in linking\nBollywood clusters. The framework and the tools used herein may be used for\nunraveling the complexity of other real world systems.\n