Relative Neighborhood Graphs Uncover the Dynamics of Social Media Engagement

  • Natalie Jane de Vries
  • Ahmed Shamsul Arefin
  • Luke Mathieson
  • Benjamin Lucas
  • Pablo Moscato
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10086)

Abstract

In this paper, we examine if the Relative Neighborhood Graph (RNG) can reveal related dynamics of page-level social media metrics. A statistical analysis is also provided to illustrate the application of the method in two other datasets (the Indo-European Language dataset and the Shakespearean Era Text dataset). Using social media metrics on the world’s ‘top check-in locations’ Facebook pages dataset, the statistical analysis reveals coherent dynamical patterns. In the largest cluster, the categories ‘Gym’, ‘Fitness Center’, and ‘Sports and Recreation’ appear closely linked together in the RNG. Taken together, our study validates our expectation that RNGs can provide a “parameter-free" mathematical formalization of proximity. Our approach gives useful insights on user behaviour in social media page-level metrics as well as other applications.

Keywords

Social networking Clustering Proximity graph Minimum spanning tree Relative neighborhood graph 

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Copyright information

© Springer International Publishing AG 2016

Authors and Affiliations

  • Natalie Jane de Vries
    • 1
  • Ahmed Shamsul Arefin
    • 1
  • Luke Mathieson
    • 1
  • Benjamin Lucas
    • 2
    • 3
  • Pablo Moscato
    • 1
  1. 1.Faculty of Engineering and Built Environment, School of Electrical Engineering and Computer ScienceThe University of NewcastleCallaghanAustralia
  2. 2.Maastricht UniversityLimburgThe Netherlands
  3. 3.Business Intelligence and Smart Services Institute (BISS) HeerlenLimburgThe Netherlands

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