Maximizing our own Centrality in Complex Networks

  • Date December 19, 2016
  • Hour 11 am
  • Room GSSI Room D
  • Speaker Lorenzo Severini (GSSI)

Lorenzo Severini, PhD candidate in Computer Science at GSSI, will give a seminar on the topic of his PhD thesis, as part of the process to obtain his PhD degree. This is the first seminar of this kind that will be given at GSSI Computer Science. Severini's research work has been carried out jointly with IMT School for Advanced Studies Lucca.


Determining what are the most important nodes in a network is one of the main problems in the field of complex network analysis. Several so-called centrality indices have been defined in the literature to try to quantitatively capture the notion of importance (or centrality) of a node within a network.
It has been experimentally observed that being central for a node, according to some centrality index, leads to several benefits to the node itself.
In this thesis, we study the problem of maximizing the centrality index of a given node by adding a limited number of edges incident to it and we show our recent results on this problem by focusing on two well-known centrality indices, namely harmonic centrality and betweenness centrality.