Modeling the popularity of twitter hashtags with master equations
Por:
Fontanelli, Oscar, Hernandez, Demian, Mansilla, Ricardo
Publicada:
1 dic 2022
Resumen:
In this work we introduce a simple mathematical model, based on master
equations, to describe the time evolution of the popularity of hashtags
on the Twitter social network. Specifically, we model the total number
of times a certain hashtag appears on user's timelines as a function of
time. Our model considers two kinds of components: those that are
internal to the network (degree distribution) as well as external
factors, such as the external popularity of the hashtag. From the master
equation, we are able to obtain explicit solutions for the mean and
variance and construct confidence regions. We propose a gamma kernel
function to model the hashtag popularity, which is quite simple and
yields reasonable results. We validate the plausibility of the model by
contrasting it with actual Twitter data obtained through the public API.
Our findings confirm that relatively simple semi-deterministic models
are able to capture the essentials of this very complex phenomenon for a
wide variety of cases. The model we present distinguishes from other
existing models in its focus on the time evolution of the total number
of times a particular hashtag has been seen by Twitter users and the
consideration of both internal and external components.
Filiaciones:
Fontanelli, Oscar:
Univ Nacl Autonoma Mexico, Ctr Invest Interdisciplinarias Ciencias & Humanid, Mexico City, DF, Mexico
Hernandez, Demian:
Univ Nacl Autonoma Mexico, Fac Ciencias, Mexico City, DF, Mexico
Mansilla, Ricardo:
Univ Nacl Autonoma Mexico, Ctr Invest Interdisciplinarias Ciencias & Humanid, Mexico City, DF, Mexico
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