Community detection in cellular network traces

Authors:
Mariya Zheleva;Paul Schmitt;Morgan Vigil;Elizabeth Belding
Affiliations:
University of California, Santa Barbara;University of California, Santa Barbara;University of California, Santa Barbara;University of California, Santa Barbara
Venue:
Proceedings of the Sixth International Conference on Information and Communications Technologies and Development: Notes - Volume 2
Year:
2013

Citing 7
Cited 0

Introduction to Data Mining, (First Edition)

Introduction to Data Mining, (First Edition)
A particle-and-density based evolutionary clustering method for dynamic networks

Proceedings of the VLDB Endowment
Avaaj Otalo: a field study of an interactive voice forum for small farmers in rural India

Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Smart Connect: last mile data connectivity for rural health facilities

Proceedings of the 4th ACM Workshop on Networked Systems for Developing Regions
Algorithms for Mining the Evolution of Conserved Relational States in Dynamic Networks

ICDM '11 Proceedings of the 2011 IEEE 11th International Conference on Data Mining
Mining Heavy Subgraphs in Time-Evolving Networks

ICDM '11 Proceedings of the 2011 IEEE 11th International Conference on Data Mining
VillageShare: facilitating content generation and sharing in rural networks

Proceedings of the 2nd ACM Symposium on Computing for Development

Quantified Score

Hi-index	0.00

Visualization

Abstract

Studies of user behavior in cellular networks have served as a knowledge base for development of critical applications and services catered to specific user needs. In this paper we examine community persistence in egocentric social graphs extracted from cellular network traces in the Cote d'Ivoire provided by Orange. The goal of our study is to inform mechanisms for improved dissemination of information by identifying subscribers or groups that can serve as information relays. We find that communities that persist in an egocentric network are independent of one another. Thus, multiple information relays can be selected from each independent community, to increase the probability that information will flow to the ego.