Ranking of nodes of networks taking into account the power function of its weight of connections

TL;DR

This paper introduces a modified HITS algorithm that considers the power function of connection weights to improve node ranking in quasi-hierarchical social networks, aligning results more closely with expert evaluations.

Contribution

A novel modification of the HITS algorithm that incorporates connection weights to better evaluate and rank influential nodes in social networks.

Findings

Modified HITS aligns with expert evaluations

Results reflect real social relationships

Improved node influence assessment

Abstract

To rank nodes in quasi-hierarchical networks of social nature, it is necessary to carry out a detailed analysis of the network and evaluate the results obtained according to all the given criteria and identify the most influential nodes. Existing ranking algorithms in the overwhelming majority estimate such networks in general, which does not allow to clearly determine the influence of nodes among themselves. In the course of the study, an analysis of the results of known algorithms for ranking the nodes of HITS, PageRank and compares the obtained data with the expert evaluation of the network. For the effective analysis of quasi-hierarchical networks, the basic algorithm of HITS is modified, which allows to evaluate and rank nodes according to the given criteria (the number of input and output links among themselves), which corresponds to the results of expert evaluation. It is shown that the received method in some cases provides results that correspond to the real social relation, and the indexes of the authorship of the nodes - pre-assigned social roles.