# Do the Young Live in a "Smaller World" Than the Old? Age-Specific Degrees of Separation in Human Communication

arXiv: https://arxiv.org/abs/1606.07556 · HTML: https://mlsanity.com/paper/1606.07556/

## Key facts

- Cited by 4 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 24 Jun 2016.

## Built on by (most cited first, 4 of 4)

- [A Comprehensive Survey on Trustworthy Graph Neural Networks: Privacy, Robustness, Fairness, and Explainability](https://mlsanity.com/paper/2204.08570/) (2022)
- [FMP: Toward Fair Graph Message Passing against Topology Bias](https://mlsanity.com/paper/2202.04187/) (2022)
- [Fair Bilevel Neural Network (FairBiNN): On Balancing fairness and accuracy via Stackelberg Equilibrium](https://mlsanity.com/paper/2410.16432/) (2024)
- [Distraction is All You Need for Fairness](https://mlsanity.com/paper/2203.07593/) (2022)

## Abstract (arXiv)

In this paper, we investigate the phenomenon of "age-specific small worlds" using data from a large-scale mobile communication network approximating interaction patterns at societal scale. Rather than asking whether two random individuals are separated by a small number of links, we ask whether individuals in specific age groups live in a small world in relation to individuals from other age groups. Our analysis shows that there is systematic variation in this age-relative small world effect. Young people live in the "smallest world," being separated from other young people and their parent's generation via a smaller number of intermediaries than older individuals. The oldest people live in the "least small world," being separated from their same age peers and their younger counterparts by a larger number of intermediaries. Variation in the small world effect is specific to age as a node attribute (being absent in the case of gender) and is consistently observed under several data robustness checks. The discovery of age-specific small worlds is consistent with well-known social mechanisms affecting the way age interacts with network connectivity and the relative prevalence of kin ties and non-kin ties observed in this network. This social pattern has significant implications for our understanding of generation-specific dynamics of information cascades, diffusion phenomena, and the spread of fads and fashions.