Community detection in cellular network traces

Mariya Zheleva, Paul Schmitt, Morgan Vigil, Elizabeth Belding

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Scopus citations

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.

Original languageEnglish (US)
Title of host publicationProceedings of the 6th International Conference on Information and Communications Technologies and Development, ICTD 2013
Pages183-186
Number of pages4
DOIs
StatePublished - 2013
Externally publishedYes
Event6th International Conference on Information and Communications Technologies and Development, ICTD 2013 - Cape Town, South Africa
Duration: Dec 7 2013Dec 10 2013

Publication series

NameACM International Conference Proceeding Series
Volume2 NOTES

Conference

Conference6th International Conference on Information and Communications Technologies and Development, ICTD 2013
Country/TerritorySouth Africa
CityCape Town
Period12/7/1312/10/13

Keywords

  • Cellular networks
  • Community detection
  • Egocentric graphs
  • Temporal graph mining

ASJC Scopus subject areas

  • Software
  • Human-Computer Interaction
  • Computer Vision and Pattern Recognition
  • Computer Networks and Communications

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