63 citations · 200 across the 10 of their papers we have counts for
10 papers
Trivial Graph Features and Classical Learning are Enough to Detect Random Anomalies
Matthieu Latapy, Stephany Rajeh
Detecting anomalies in link streams that represent various kinds of interactions is an important research topic with crucial applications. Because of the lack of ground truth data,…
Comparative evaluation of community-aware centrality measures
Stephany Rajeh, Marinette Savonnet, Eric Leclercq +1
Influential nodes play a critical role in boosting or curbing spreading phenomena in complex networks. Numerous centrality measures have been proposed for identifying and ranking t…
Identifying Influential Nodes Using Overlapping Modularity Vitality
Stephany Rajeh, Marinette Savonnet, Eric Leclercq +1
It is of paramount importance to uncover influential nodes to control diffusion phenomena in a network. In recent works, there is a growing trend to investigate the role of the com…
Comparing Community-aware Centrality Measures in Online Social Networks
Stephany Rajeh, Marinette Savonnet, Eric Leclercq +1
Identifying key nodes is crucial for accelerating or impeding dynamic spreading in a network. Community-aware centrality measures tackle this problem by exploiting the community st…
Analyzing Community-aware Centrality Measures Using The Linear Threshold Model
Stephany Rajeh, Ali Yassin, Ali Jaber +1
Targeting influential nodes in complex networks allows fastening or hindering rumors, epidemics, and electric blackouts. Since communities are prevalent in real-world networks, com…
How Correlated are Community-aware and Classical Centrality Measures in Complex Networks?
Stephany Rajeh, Marinette Savonnet, Eric Leclercq +1
Unlike classical centrality measures, recently developed community-aware centrality measures use a network's community structure to identify influential nodes in complex networks.…
Investigating Centrality Measures in Social Networks with Community Structure
Stephany Rajeh, Marinette Savonnet, Eric Leclercq +1
Centrality measures are crucial in quantifying the influence of the members of a social network. Although there has been a great deal of work dealing with this issue, the vast majo…
Modularity-based Backbone Extraction in Weighted Complex Networks
Stephany Rajeh, Marinette Savonnet, Eric Leclercq +1
The constantly growing size of real-world networks is a great challenge. Therefore, building a compact version of networks allowing their analyses is a must. Backbone extraction te…
Characterizing the Interactions Between Classical and Community-aware Centrality Measures in Complex Networks
Stephany Rajeh, Marinette Savonnet, Eric Leclercq +1
Identifying vital nodes in networks exhibiting a community structure is a fundamental issue. Indeed, community structure is one of the main properties of real-world networks. Recen…
Interplay Between Hierarchy and Centrality in Complex Networks
Stephany Rajeh, Marinette Savonnet, Eric Leclercq +1
Hierarchy and centrality are two popular notions used to characterize the importance of entities in complex systems. Indeed, many complex systems exhibit a natural hierarchical str…