SELHR: A Novel Epidemic-Based Model for Information Propagation in Complex Networks

Table 1

Analysis of different propagation dynamics models.

Model	Node states	Parameters	Heterogeneous	Structure	Advantage
SIVR [33]	4	4	N	Unidirectional	Individuals can be exposed to new information in the dissemination of information influence.
SIVRS [34]	5	9	N	Unidirectional	Considering the influence of network node degree and mortality.
SIHR [35]	4	5	N	Bidirectional	Infectious disease model with forgetting mechanism H.
SHIR [36]	5	3	N	Unidirectional	A dynamic model of competitive dual information diffusion.
SPIR [37]	3	2	N	Unidirectional	The concept of potential spreader set is presented.
SICR [38]	4	5	N	Unidirectional	Present a counterattack group in rumor propagation model.
ESIS [39]	3	3	N	Unidirectional	Information disseminated in online social networks includes expressions of emotion.
SEIRV [40]	4	7	Y	Unidirectional	The impact of the cost of vaccination and disease treatment on the vaccination coverage rate is analyzed.
SIR/V [41]	7	5	Y	Unidirectional	Two layers SIR/V epidemic model is considered, and individuals are parted as an unaware and an aware state
SHIR [42]	4	10	Y	Unidirectional	Two dynamical systems are designed in homogeneous and heterogeneous networks by utilizing mean field equations.
SELHR	5	9	Y	Bidirectional	Transform rate between different types of propagation nodes is considered.