A Framework for Analysing Dynamic Communities in Large-scale Social Networks

Vítor Cerqueira, Márcia Oliveira, João Gama

Abstract

Telecommunications companies must process large-scale social networks that reveal the communication patterns among their customers. These networks are dynamic in nature as new customers appear, old customers leave, and the interaction among customers changes over time. One way to uncover the evolution patterns of such entities is by monitoring the evolution of the communities they belong to. Large-scale networks typically comprise thousands, or hundreds of thousands, of communities and not all of them are worth monitoring, or interesting from the business perspective. Several methods have been proposed for tracking the evolution of groups of entities in dynamic networks but these methods lack strategies to effectively extract knowledge and insight from the analysis. In this paper we tackle this problem by proposing an integrated business-oriented framework to track and interpret the evolution of communities in very large networks. The framework encompasses several steps such as network sampling, community detection, community selection, monitoring of dynamic communities and rule-based interpretation of community evolutionary profiles. The usefulness of the proposed framework is illustrated using a real-world large-scale social network from a major telecommunications company.

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Paper Citation


in Harvard Style

Cerqueira V., Oliveira M. and Gama J. (2015). A Framework for Analysing Dynamic Communities in Large-scale Social Networks . In Proceedings of the 17th International Conference on Enterprise Information Systems - Volume 1: ICEIS, ISBN 978-989-758-096-3, pages 235-242. DOI: 10.5220/0005345602350242


in Bibtex Style

@conference{iceis15,
author={Vítor Cerqueira and Márcia Oliveira and João Gama},
title={A Framework for Analysing Dynamic Communities in Large-scale Social Networks},
booktitle={Proceedings of the 17th International Conference on Enterprise Information Systems - Volume 1: ICEIS,},
year={2015},
pages={235-242},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0005345602350242},
isbn={978-989-758-096-3},
}


in EndNote Style

TY - CONF
JO - Proceedings of the 17th International Conference on Enterprise Information Systems - Volume 1: ICEIS,
TI - A Framework for Analysing Dynamic Communities in Large-scale Social Networks
SN - 978-989-758-096-3
AU - Cerqueira V.
AU - Oliveira M.
AU - Gama J.
PY - 2015
SP - 235
EP - 242
DO - 10.5220/0005345602350242