Relative Neighborhood Graphs Uncover the Dynamics of Social Media Engagement View Full Text


Ontology type: schema:Chapter     


Chapter Info

DATE

2016

AUTHORS

Natalie Jane de Vries , Ahmed Shamsul Arefin , Luke Mathieson , Benjamin Lucas , Pablo Moscato

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. More... »

PAGES

283-297

Book

TITLE

Advanced Data Mining and Applications

ISBN

978-3-319-49585-9
978-3-319-49586-6

Author Affiliations

From Grant

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/978-3-319-49586-6_19

DOI

http://dx.doi.org/10.1007/978-3-319-49586-6_19

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1084904755


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