Abstract
A more realistic mathematical influenza model including dynamics of Twitter, which may reduce and increase the spread of influenza, is introduced. The basic reproductive number is derived and the stability of the steady states is proved. The existence of Hopf bifurcation are also demonstrated by analyzing the associated characteristic equation. Furthermore, numerical simulations and sensitivity analysis of relevant parameters are also carried out. Our results show that the impact posed by the negative information of Twitter is not significant than the impact posed by the positive information of Twitter on influenza while the impact posed by the negative information of Twitter on the influenza virus is still extraordinary.
Highlights
Twitter is an online social networking service that enables users to send and read short 140-character messages called “tweets”
The site is largely used to daily chatter, conversation, and debate about information, or to allow ones to understand the world by Daily News (Java et al 2007)
Twitter’s users who are increasingly diverse in age, ethnicity and gender may see the messages of other followers and go along with these users (Sanderson 2014)
Summary
Twitter is an online social networking service that enables users to send and read short 140-character messages called “tweets”. T1(t) and T2(t) represent the number of tweets that all of them provide positive and negative information about influenza at time t, respectively. The rate that tweets become outdated infectious individuals gain permanent immunity to that strain of influenza, p is the ratio that individuals may provide positive information about influenza during an epidemic season.
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