activity
20172020
most citedA Faster Method to Estimate Closeness Centrality Ranking

14 citations · 46 across the 7 of their papers we have counts for

collaborators

9 papers

cs.SI202013 cited

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…

cs.CY2019

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…

cs.CY2018

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…

cs.SI2018

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…

cs.SI20175 cited

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…

cs.SI20176 cited

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…