Top Leaders Community Detection Approach in Information Networks
Much of the data of scientific interest, particularly when independence of data is not assumed, can be represented in the form of information networks where data nodes are joined together to form edges corresponding to some kind of associations or relationships. Such information networks abound, like protein interactions in biology, web page hyperlink connections in information retrieval on the Web, cellphone call graphs in telecommunication, co-authorships in bibliometrics, crime event connections in criminology, etc. All these networks, also known as social networks, share a common property, the formation of connected groups of information nodes, called community structures. These groups are densely connected nodes with sparse connections outside the group. Finding these communities is an important task for the discovery of underlying structures in social networks, and has recently attracted much attention in data mining research.
In this paper, we present Top Leaders, a new community mining approach that, simply put, regards a community as a set of followers congregating around a potential leader. Our algorithm starts by identifying promising leaders in a given network then iteratively assembles followers to their closest leaders to form communities, and subsequently finds new leaders in each group around which to gather followers again until convergence. Our intuitions are based on proven observations in social networks and the results are very promising. Experimental results on benchmark networks verify the feasibility and effectiveness of our new community mining approach.
Citation
R. Rabbany,
J. Chen,
O. Zaiane.
"Top Leaders Community Detection Approach in Information Networks". SNA-KDD Workshop on Social Network Mining and Analysis, July 2010.
| Keywords: |
|
| Category: |
In Workshop |
BibTeX
@misc{Rabbany+al:10,
author = {Reihaneh Rabbany and Jiyang Chen and Osmar R. Zaiane},
title = {Top Leaders Community Detection Approach in Information Networks},
booktitle = {SNA-KDD Workshop on Social Network Mining and Analysis},
year = 2010,
}Last Updated: January 15, 2020
Submitted by Sabina P 
