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