Proportional Selection in Networks

TL;DR

This paper introduces methods for selecting influential and diverse nodes in a network, balancing influence and diversity, with theoretical analysis and experimental validation.

Contribution

It proposes two novel approaches for proportional node selection, addressing influence and diversity simultaneously, with theoretical insights and empirical evaluation.

Findings

The approaches effectively identify influential nodes reflecting network diversity.

Theoretical analysis supports the methods' validity.

Experimental results demonstrate improved selection quality.

Abstract

We address the problem of selecting $k$ representative nodes from a network, aiming to achieve two objectives: identifying the most influential nodes and ensuring the selection proportionally reflects the network's diversity. We propose two approaches to accomplish this, analyze them theoretically, and demonstrate their effectiveness through a series of experiments.