Liquidity on Web Dynamic Network

TL;DR

This paper introduces a dynamic fluid-based model for analyzing the evolution of web networks with correlated topics, enabling real-time understanding of complex, large-scale web structures.

Contribution

It presents a novel, fully evolutive fluid-dynamic model for web networks that overcomes static model limitations and allows efficient numerical simulation of large, dynamic systems.

Findings

Model effectively captures web network evolution over time

Numerical schemes are efficient for large-scale networks

The model uses a simple conservation law framework

Abstract

Nowadays, the exponentially growing of the Web renders the problem of correlation among different topics of paramount importance. The proposed model can be used to study the evolution of network depicted by different topics on the web correlated by a dynamic "fluid" of tags among them. The fluid-dynamic model depicted is completely evolutive, thus it is able to describe the dynamic situation of a network at every instant of time. This overcomes the difficulties encountered by many static models. The theory permits the development of efficient numerical schemes also for very large networks. This is possible since dynamic flow at junctions is modeled in a simple and computationally convenient way (resorting to a linear programming problem). The obtained model consists of a single conservation law and is on one side simple enough to permit a complete understanding, on the other side reach enough to detect the evolution of the dynamic network.