Relative Neighborhood Graphs Uncover the Dynamics of Social Media Engagement

N.J. de Vries, A.S. Arefin, L. Mathieson, Benjamin Lucas, P. Moscato

Research output: Chapter in Book/Report/Conference proceedingChapterAcademic

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.
Original languageEnglish
Title of host publicationAdvanced Data Mining and Applications
Subtitle of host publication12th International Conference, ADMA 2016, Gold Coast, QLD, Australia, December 12-15, 2016, Proceedings
PublisherSpringer
Pages283-297
Edition12
ISBN (Print)978-3-319-49586-6
DOIs
Publication statusPublished - 2016
Event12th International Conference, ADMA 2016 - Gold Coast, Australia
Duration: 12 Dec 201615 Dec 2016

Publication series

SeriesLecture Notes in Computer Science
Volume10086
ISSN0302-9743

Conference

Conference12th International Conference, ADMA 2016
Abbreviated titleADMA 2016
CountryAustralia
Period12/12/1615/12/16

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