A Dynamical Model of Twitter Activity Profiles
File(s)
Accepted version
Author(s)
Huynh, Hoai Nguyen
Legara, Erika Fille
Monterola, Christopher
Type
Conference Paper
Abstract
The advent of the era of Big Data has allowed many researchers to dig into
various socio-technical systems, including social media platforms. In
particular, these systems have provided them with certain verifiable means to
look into certain aspects of human behavior. In this work, we are specifically
interested in the behavior of individuals on social media platforms---how they
handle the information they get, and how they share it. We look into Twitter to
understand the dynamics behind the users' posting activities---tweets and
retweets---zooming in on topics that peaked in popularity. Three mechanisms are
considered: endogenous stimuli, exogenous stimuli, and a mechanism that
dictates the decay of interest of the population in a topic. We propose a model
involving two parameters $\eta^\star$ and $\lambda$ describing the tweeting
behaviour of users, which allow us to reconstruct the findings of Lehmann et
al. (2012) on the temporal profiles of popular Twitter hashtags. With this
model, we are able to accurately reproduce the temporal profile of user
engagements on Twitter. Furthermore, we introduce an alternative in classifying
the collective activities on the socio-technical system based on the model.
various socio-technical systems, including social media platforms. In
particular, these systems have provided them with certain verifiable means to
look into certain aspects of human behavior. In this work, we are specifically
interested in the behavior of individuals on social media platforms---how they
handle the information they get, and how they share it. We look into Twitter to
understand the dynamics behind the users' posting activities---tweets and
retweets---zooming in on topics that peaked in popularity. Three mechanisms are
considered: endogenous stimuli, exogenous stimuli, and a mechanism that
dictates the decay of interest of the population in a topic. We propose a model
involving two parameters $\eta^\star$ and $\lambda$ describing the tweeting
behaviour of users, which allow us to reconstruct the findings of Lehmann et
al. (2012) on the temporal profiles of popular Twitter hashtags. With this
model, we are able to accurately reproduce the temporal profile of user
engagements on Twitter. Furthermore, we introduce an alternative in classifying
the collective activities on the socio-technical system based on the model.
Date Issued
2015-12-31
Date Acceptance
2015-06-01
Citation
1, 5, pp.49-57
Start Page
49
End Page
57
Journal / Book Title
1
Volume
5
Copyright Statement
© 2015 ACM. This is the author's version of the work. It is posted here by permission of ACM for your personal use. Not for redistribution. The definitive version was published in HT '15 Proceedings of the 26th ACM Conference on Hypertext & Social Media https://dl.acm.org/citation.cfm?doid=2700171.2791029
Identifier
http://arxiv.org/abs/1508.07097v1
Source
26th ACM Conference on Hypertext and Social Media
Subjects
cs.SI
cs.SI
cs.CY
cs.HC
physics.soc-ph
J.2; J.4; I.6
Notes
10 pages, 5 figures