14 citations · 73 across the 18 of their papers we have counts for
16 papers · 1 filter
Centrality Measures in Complex Networks: A Survey
Akrati Saxena, Sudarshan Iyengar
In complex networks, each node has some unique characteristics that define the importance of the node based on the given application-specific context. These characteristics can be…
Estimating Shell-Index in a Graph with Local Information
Akrati Saxena, S. R. S. Iyengar
For network scientists, it has always been an interesting problem to identify the influential nodes in a given network. The k-shell decomposition method is a widely used method whi…
Global Rank Estimation
Akrati Saxena, S. R. S. Iyengar
In real world complex networks, the importance of a node depends on two important parameters: 1. characteristics of the node, and 2. the context of the given application. The curre…
Degree Ranking Using Local Information
Akrati Saxena, Ralucca Gera, S. R. S. Iyengar
Most real world dynamic networks are evolved very fast with time. It is not feasible to collect the entire network at any given time to study its characteristics. This creates the…
A Faster Method to Estimate Closeness Centrality Ranking
Akrati Saxena, Ralucca Gera, S. R. S. Iyengar
Closeness centrality is one way of measuring how central a node is in the given network. The closeness centrality measure assigns a centrality value to each node based on its acces…
MPC meets SNA: A Privacy Preserving Analysis of Distributed Sensitive Social Networks
Varsha Bhat Kukkala, S. R. S Iyengar
In this paper, we formalize the notion of distributed sensitive social networks (DSSNs), which encompasses networks like enmity networks, financial transaction networks, supply cha…
Evolving Models for Meso-Scale Structures
Akrati Saxena, S. R. S. Iyengar
Real world complex networks are scale free and possess meso-scale properties like core-periphery and community structure. We study evolution of the core over time in real world net…
Rank me thou shalln't Compare me
Akrati Saxena, Vaibhav Malik, S. R. S. Iyengar
Centrality measures have been defined to quantify the importance of a node in complex networks. The relative importance of a node can be measured using its centrality rank based on…
Estimating the Degree Centrality Ranking of a Node
Akrati Saxena, Vaibhav Malik, S. R. S. Iyengar
Complex networks have gained more attention from the last few years. The size of real-world complex networks, such as online social networks, WWW network, collaboration networks, i…
Shifting Behaviour of Users: Towards Understanding the Fundamental Law of Social Networks
Yayati Gupta, S. R. S. Iyengar, Jaspal Singh Saini +1
Social Networking Sites (SNSs) are powerful marketing and communication tools. There are hundreds of SNSs that have entered and exited the market over time. The coexistence of mult…
Pseudo-Cores: The Terminus of an Intelligent Viral Meme's Trajectory
Yayati Gupta, Debarati Das, S. R. S. Iyengar
Comprehending the virality of a meme can help us in addressing the problems pertaining to disciplines like epidemiology and digital marketing. Therefore, it is not surprising that…
Modeling Memetics using Edge Diversity
Yayati Gupta, Akrati Saxena, Debarati Das +1
The study of meme propagation and the prediction of meme trajectory are emerging areas of interest in the field of complex networks research. In addition to the properties of the m…
An Efficient Heuristic for Betweenness-Ordering
Rishi Ranjan Singh, Shubham Chaudhary, Manas Agarwal
Centrality measures, erstwhile popular amongst the sociologists and psychologists, have seen broad and increasing applications across several disciplines of late. Amongst a plethor…
Prediction Of Arrival Of Nodes In A Scale Free Network
S. M. Vijay Mahantesh, Sudarshan Iyengar, M. Vijesh +2
Most of the networks observed in real life obey power-law degree distribution. It is hypothesized that the emergence of such a degree distribution is due to preferential attachment…
A Navigation Algorithm Inspired by Human Navigation
Vijesh M., Sudarshan Iyengar, Vijay Mahantesh +2
Human navigation has been a topic of interest in spatial cognition from the past few decades. It has been experimentally observed that humans accomplish the task of way-finding a d…
A Lookahead algorithm to compute Betweenness Centrality
B Vignesh, Siddharth S, Shridhar Ramachandran +2
The Betweenness Centrality index is a very important centrality measure in the analysis of a large number of networks. Despite its significance in a lot of interdisciplinary applic…