  Existing centrality measures for social network analysis suggest the
im-portance of an actor and give consideration to actor's given structural
position in a network. These existing measures suggest specific attribute of an
actor (i.e., popularity, accessibility, and brokerage behavior). In this study,
we propose new hybrid centrality measures (i.e., Degree-Degree,
Degree-Closeness and Degree-Betweenness), by combining existing measures (i.e.,
degree, closeness and betweenness) with a proposition to better understand the
importance of actors in a given network. Generalized set of measures are also
proposed for weighted networks. Our analysis of co-authorship networks dataset
suggests significant correlation of our proposed new centrality measures
(especially weighted networks) than traditional centrality measures with
performance of the scholars. Thus, they are useful measures which can be used
instead of traditional measures to show prominence of the actors in a network.
