14 citations · 73 across the 18 of their papers we have counts for
23 papers
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…
Investigating Ortega Hypothesis in Q&A portals: An Analysis of StackOverflow
Anamika Chhabra, S. R. S. Iyengar
Ortega Hypothesis considers masses, i.e., a large number of average people who are not specially qualified as being instrumental in any system's progress. This hypothesis has been…
Capturing Knowledge Triggering in Collaborative Settings
Anamika Chhabra, S. R. Sudarshan Iyengar
In collaborative knowledge building settings, the existing knowledge in the system is perceived to set stage for the manifestation of more knowledge, termed as the phenomenon of tr…
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…
How Does Knowledge Come By?
Anamika Chhabra, S. R. S. Iyengar
Although the amount of knowledge that the humans possess has been gradually increasing, we still do not know the procedure and conditions that lead to the creation of new knowledge…
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…
A Framework for Textbook Enhancement and Learning using Crowdsourced Annotations
Anamika Chhabra, S. R. S. Iyengar, Poonam Saini +1
Despite a significant improvement in the educational aids in terms of effective teaching-learning process, most of the educational content available to the students is less than op…
Ecosystem: A Characteristic Of Crowdsourced Environments
Anamika Chhabra, S. R. S. Iyengar, Poonam Saini +2
The phenomenal success of certain crowdsourced online platforms, such as Wikipedia, is accredited to their ability to tap the crowd's potential to collaboratively build knowledge.…
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…
Navigability on Networks: A Graph Theoretic Perspective
Rishi Ranjan Singh, Shreyas Balakuntala, Sudarshan Iyengar
Human navigation has been of interest to psychologists and cognitive scientists since the past few decades. It was in the recent past that a study of human navigational strategies…
Human Navigational Performance in a Complex Network with Progressive Disruptions
Amitash Ramesh, Soumya Ramesh, Sudarshan Iyengar +1
The current paper is an investigation towards understanding the navigational performance of humans on a network when the "landmark" nodes are blocked. We observe that humans learn…
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…