Given a connected graph G=(V, E), where V denotes the set of nodes and E the set of edges
of the graph, the length (that is, the number of edges) of the shortest path between two …

Analyzing the structure of a social network helps in gaining insights into interactions and
relationships among users while revealing the patterns of their online behavior. Network …

Based on the performance of entire social networks, anomaly analysis for evolving social
networks generally ignores the otherness of the evolutionary behaviors of different nodes …

As we are in the age of big data, graph data become bigger. A big graph normally has an
overwhelming number of edges. Existing metrics of edge centrality are not quite suitable for …

Centrality measures or indicators of centrality identify most relevant nodes of graphs.
Although optimized algorithms exist for computing of most of them, they are still time …

Influence measures, like social network analysis (SNA) metrics, Twitter social parameters,
sentiment score and influence maximisation, are used in the literature in order to provide a …

Over the last 15 years, interest in narrative as a concept for supporting national defense has
grown considerably. But efforts to win the battle of the narrative have yielded limited results …

It has long been an area of interest to identify important vertices in social networks.
Closeness centrality is one of the most popular measures of centrality of vertices. Generally …

The study of any complex system in the form of a network structure has always been an
efficient approach, being the underlying aspect of graph theory. For the topological and …

The digitization of the world has also led to a digitization of communication processes.
Traditional research methods fall short in understanding communication in digital worlds as …