Shortest Path Discovery in the Multi-layered Social Network

TL;DR

This paper introduces two algorithms for finding shortest paths in multi-layered social networks, addressing the complexity of multiple relation types, with experimental validation on the DBLP dataset.

Contribution

It proposes novel algorithms for shortest path discovery in multi-layered social networks, including pre-processing and real-time processing approaches.

Findings

Algorithms effectively handle multi-layered relations.

Experimental results demonstrate efficiency on DBLP data.

Pre-processing and on-the-fly methods have different trade-offs.

Abstract

Multi-layered social networks consist of the fixed set of nodes linked by multiple connections. These connections may be derived from different types of user activities logged in the IT system. To calculate any structural measures for multi-layered networks this multitude of relations should be coped with in the parameterized way. Two separate algorithms for evaluation of shortest paths in the multi-layered social network are proposed in the paper. The first one is based on pre-processing - aggregation of multiple links into single multi-layered edges, whereas in the second approach, many edges are processed 'on the fly' in the middle of path discovery. Experimental studies carried out on the DBLP database converted into the multi-layered social network are presented as well.