Measuring how new nodes compete with old in growing networks
Measuring the impact of hits
Social and Information Networks
Summary
Many networks grow when new points and connections are added over time, like new websites linking on the internet or movies gaining viewers. People often think these new points compete for attention and links, but it hasn’t been clearly measured before. The authors created a method to measure this competition and tested it on real-world examples like online news and movie audiences. They found that while new additions do affect the network, they never completely push out the existing parts.
What this means in practice
- •For e-commerce platform teams: Quantify how new products or sellers compete with existing ones in online marketplaces to better tailor recommendation algorithms and inventory management.
- •For digital marketing analysts: Measure how new online content impacts engagement with existing content to optimize content release schedules and promotional strategies.
Authors
Matúš Medo, Liudmila Rozanova
Abstract
Many real systems can be represented as growing networks where new nodes and links gradually emerge. The Barabási-Albert model for growing networks, and many models inspired by it, are based on the idea that nodes compete for links. However, the strength and the very presence of this competition have not been tested. We propose a robust statistical approach to quantify how strongly nodes compete for links, and apply it to data from various real systems---commenting on online news and cinema attendance data. We find a range of possible behaviors, from the perfectly elastic case, where new entrants shape network growth in a way that leaves the rest of the system unaffected, to an intermediate case where new entrants measurably affect the rest. Perfect competition is never observed. These findings have direct implications for complex systems modeling and e-commerce applications.