Search Results for author:
Found 5 papers, 0 papers with code
DCC: A Cascade based Approach to Detect Communities in Social Networks
In this paper, we have introduced a novel method called \emph{Disjoint Community detection using Cascades (DCC)} which demonstrates the effectiveness of a new local density based tie strength measure on detecting communities.
Beyond Information Exchange: An Approach to Deploy Network Properties for Information Diffusion
Although several mathematical models have been developed till date, but previous works lacked systematic analysis and exploration of the influence of neighborhood for information diffusion.
Direct Comparative Analysis of Nature-inspired Optimization Algorithms on Community Detection Problem in Social Networks
Nature-inspired optimization Algorithms (NIOAs) are nowadays a popular choice for community detection in social networks.
The Ties that matter: From the perspective of Similarity Measure in Online Social Networks
Online Social Networks have embarked on the importance of connection strength measures which has a broad array of applications such as, analyzing diffusion behaviors, community detection, link predictions, recommender systems.
Towards Direct Comparison of Community Structures in Social Networks
Community detection algorithms are in general evaluated by comparing evaluation metric values for the communities obtained with different algorithms.
