Abstract
Many real-world networks have a natural tripartite structure. Investigating the structure and the behavior of actors in these networks is useful to gain a deeper understanding of their behavior and dynamics. In our paper, we describe an evolving tripartite network using a network model with preferential growth mechanisms and different rules for changing the strength of nodes and the weights of edges. We analyze the characteristics of the strength distribution and behavior of selected nodes and selected actors in this tripartite network. The distributions of these analyzed characteristics follow the power-law under different modeled conditions. Performed simulations have confirmed all these results. Despite its simplicity, the model expresses well the basic properties of the modeled network. It can provide further insights into the behavior of systems with more complex behaviors, such as the multi-actor e-commerce system that we have used as a real basis for the validation of our model.
Highlights
Complex network structures can be detected in many systems that can be found in the field like biology, ecology, social sciences, or large information infrastructures
Complex networks play an essential role in a wide range of disciplines such as social and behavioral sciences, biology, economics, industrial engineering, information technology, and more
We use a model of evolving weighted tripartite network with preferential growth mechanisms and different rules for changing the strength of nodes and edge weights
Summary
Complex network structures can be detected in many systems that can be found in the field like biology, ecology, social sciences, or large information infrastructures. Online systems based on Internet technology have mostly complex arrangement and different relationships between the entities, which affects their properties. These topological functions of networks prove to be extremely important as they have a strong impact on the characteristics of networks such as robustness or vulnerability [1,2] and others. The development of a complex network topology was considered as an output of a dynamic system with state variables associated with edges and nodes; see [3,4,5]. The macroscopic behavior of these complex systems can often be reproduced using a suitable network model, with very few assumptions about the components themselves, as shown
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
