Study of the US road network based on social network analysis

Elie Ngomseu Mambou, Samuel Nlend, Harold Liu

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

2 Citations (Scopus)

Abstract

The complexity of big data structures and networks demands more research in terms of analysing and representing data for a better comprehension and usage. In this regard, there are several types of model to represent a structure. The aim of this article is to use a social network topology to analyse road network for the following States in the United States (US): California, Pennsylvania and Texas. Our approach mainly focuses on clustering of road network data in order to create 'communities'.

Original languageEnglish
Title of host publication2017 IEEE AFRICON
Subtitle of host publicationScience, Technology and Innovation for Africa, AFRICON 2017
EditorsDarryn R. Cornish
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages974-978
Number of pages5
ISBN (Electronic)9781538627754
DOIs
Publication statusPublished - 3 Nov 2017
Externally publishedYes
EventIEEE AFRICON 2017 - Cape Town, South Africa
Duration: 18 Sept 201720 Sept 2017

Publication series

Name2017 IEEE AFRICON: Science, Technology and Innovation for Africa, AFRICON 2017

Conference

ConferenceIEEE AFRICON 2017
Country/TerritorySouth Africa
CityCape Town
Period18/09/1720/09/17

Keywords

  • Community structure
  • GraphX
  • MLib
  • Road network
  • Social network analysis (SNA)
  • Spark
  • Tableau

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