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Engagement in Motion: Exploring Short Term Dynamics in Page-Level Social Media Metrics

Lucas, Benjamin; Arefin, Ahmed Shamsul; Vries, Natalie Jane de; Berretta, Regina; Carlson, Jamie; Moscato, Pablo

Authors

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BENJAMIN LUCAS Benjamin.Lucas@nottingham.ac.uk
Research & Knowledge Exchangedevelopment Manager

Ahmed Shamsul Arefin

Natalie Jane de Vries

Regina Berretta

Jamie Carlson

Pablo Moscato



Abstract

Using page-level metrics of a randomly selected group of 15,625 among the top 100,000 Facebook check-in locations which rank high in terms of customer engagement, we explore if the short-term dynamical information on these metrics could deliver, via a clustering approach, some new insights for marketing decision making. Using a highly-scalable clustering algorithm, statistical methods, and combinatorial optimization metaheuristics based on memetic algorithms, we have observed that some pages naturally cluster with others that share the same user-defined category. Our results highlight the need of suggesting other further " meta-categories " that encompass several user-reported categories for pages and that a priori geographical segmentation might be necessary to investigate more relevant patterns that take into account seasonal variability of behaviours and physical proximity.

Citation

Lucas, B., Arefin, A. S., Vries, N. J. D., Berretta, R., Carlson, J., & Moscato, P. (2015). Engagement in Motion: Exploring Short Term Dynamics in Page-Level Social Media Metrics. In 2014 IEEE Fourth International Conference on Big Data and Cloud Computingdoi:10.1109/bdcloud.2014.56

Conference Name 2014 IEEE International Conference on Big Data and Cloud Computing (BdCloud)
Start Date Dec 3, 2014
End Date Dec 5, 2014
Acceptance Date Dec 3, 2014
Online Publication Date Dec 3, 2014
Publication Date Feb 9, 2015
Deposit Date Mar 5, 2019
Publisher Institute of Electrical and Electronics Engineers
Book Title 2014 IEEE Fourth International Conference on Big Data and Cloud Computing
ISBN 9781479967193
DOI https://doi.org/10.1109/bdcloud.2014.56
Keywords Page-level metrics; combinatorial optimisation; marketing decision making; memetic algorithms
Public URL https://nottingham-repository.worktribe.com/output/1608262
Publisher URL https://ieeexplore.ieee.org/document/7034813