The present paper illustrates a methodological strategy to address the first phases of the
policy cycle–namely agenda setting, impact analysis, and policy formulation–with the aim of …

Node connectivity plays a central role in temporal network analysis. We provide a broad
study of various concepts of walks in temporal graphs, that is, graphs with fixed vertex sets …

Measures of centrality of vertices in a network are usually defined solely on the basis of the
network structure. In highly dynamic networks, where vertices appear and disappear and …

The betweenness centrality of a graph vertex measures how often this vertex is visited on
shortest paths between other vertices of the graph. In the analysis of many real-world graphs …

The betweenness centrality of a vertex v is an important centrality measure that quantifies
how many optimal paths between pairs of other vertices visit v. Computing betweenness …

In static graphs, the betweenness centrality of a graph vertex measures how many times this
vertex is part of a shortest path between any two graph vertices. Betweenness centrality is …

Consider planning a trip in a train network. In contrast to, say, a road network, the edges are
temporal, ie, they are only available at certain times. Another important difficulty is that trains …

Betweeness centrality is one of the most important concepts in graph analysis. It was
recently extended to link streams, a graph generalization where links arrive over time …

In the study of temporal graphs, only paths respecting the flow of time are relevant. In this
context, many concepts of walk disjointness have been proposed over the years and the …

The search for biomarkers of diseases has traditionally involved analyzing disease data as a
whole. But this approach has largely ignored the significance of disease progression at …