Aug 2026· Proceedings of the National Academy of Sciences of the United States of America· Vol 123 35, pp.
e2603299123
· 0 citations· 34 references
Medicine
TL;DR
It is shown that the more people who share a common friend, the more connected that person tends to be, and an expression quantifying this progression is derived.
Abstract
The Friendship Paradox states that, on average, your friends have more friends than you do. We extend this to common friends-those who appear in multiple people's friend lists. We show that the more people who share a common friend, the more connected that person tends to be, and we derive an expression quantifying this progression. In a regional Facebook network, a common friend to three randomly sampled individuals has on average more friends than 99.9% of the network. In a citation network, a source cited by any two of a random sample of papers has on average more citations than 99.99% of cited works. This power of common friends is most pronounced when few nodes hold disproportionate shares of ties, typical of networks involving superspreaders of disease, mega-influencers online, and highly connected nodes in neural networks. We discuss implications for network sampling, targeted interventions, social perception, and network dynamics.
We provide a first causal analysis of the behavioral consequences of the friendship paradox—the fact that people’s friends in a network have more connections than average. We find that people’s behavior is biased by their network position: they do not best respond to what they should infer the average behavior of the p...
Gary Charness, Francesco Feri, M. Jackson et al.· CESifo working papers· 0 citations
Social networks in which algorithms actively influence humans through personal recommendations are ubiquitous. While opinion dynamics is an established tool to analyze these systems, existing models typically do not capture how individual agents process personal recommendations. In this work, we introduce a model for p...
Philipp Grünter, K. H. Johansson, Angela Fontan· 0 citations
Many real systems can be represented as growing networks where new nodes and links gradually emerge. The Barab\'asi-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....
A large-scale empirical analysis of more than 50,000 English-language starter packs and over 600,000 associated users shows that starter packs form a highly interconnected ecosystem with substantial overlap across packs that largely reflects pre-existing communities.
Andrea Failla, V. L. S. Freitas, Giulio Rossetti et al.· 1 citation
This work develops a multiagent simulation of a popular social network, Reddit, and uses millions of posts from users on the platform to model content-sharing on the platform.
Swapneel Mehta, Bogdan State, Richard Bonneau et al.· 1 citation
Online social networks are used by many people. These Social networks allowtheir users to connect bymeans of various link types in which the network gives an opportunity for people to list details about themselves that are relevant to the nature of the network. Here there is a chance of inference when user released som...
T. Bindu· Journal of Science & Technol...· 1 citation
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