Showing papers on "Katz centrality published in 1999"
TL;DR: In this paper, the authors extend the standard network centrality measures of degree, closeness and betweenness to apply to groups and classes as well as individuals, and propose a measure of group centrality efficiency, which indicates the extent to which a group's centrality is principally due to a small subset of its members.
Abstract: This paper extends the standard network centrality measures of degree, closeness and betweenness to apply to groups and classes as well as individuals. The group centrality measures will enable researchers to answer such questions as ‘how central is the engineering department in the informal influence network of this company?’ or ‘among middle managers in a given organization, which are more central, the men or the women?’ With these measures we can also solve the inverse problem: given the network of ties among organization members, how can we form a team that is maximally central? The measures are illustrated using two classic network data sets. We also formalize a measure of group centrality efficiency, which indicates the extent to which a group's centrality is principally due to a small subset of its members.
592 citations
TL;DR: A new model for the diffusion of information through heterogeneous social networks is discussed, an improvement on earlier ones because it allows a transmitter of information to retain that information after telling it to somebody else.
Abstract: This paper discusses a new model for the diffusion of information through heterogeneous social networks. In earlier models, when information was given by one actor to another the transmitter did not retain the information. The new model is an improvement on earlier ones because it allows a transmitter of information to retain that information after telling it to somebody else. Consequently, the new model allows more actors to have information during the information diffusion process. The model provides predictions of diffusion times in a given network at the global, dyadic, and individual levels. This leads to straightforward generalizations of network measures, such as closeness centrality and betweenness centrality, for research problems that focus on the efficiency of information transfer in a network. We analyze in detail how information diffusion times and centrality measures depend on a series of network measures, such as degrees and bridges. One important finding is that predictions about the time ...
67 citations