# Time varying networks and the weakness of strong ties

arXiv: https://arxiv.org/abs/1303.5966 · HTML: https://mlsanity.com/paper/1303.5966/

## Key facts

- Cited by 3 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 24 Mar 2013.

## Built on by (most cited first, 3 of 3)

- [Formalisation of Action with Durations in Answer Set Programming](https://mlsanity.com/paper/2109.08305/) (2021)
- [Decentralised Federated Learning over Temporal Networks: The Role of Heterogeneities](https://mlsanity.com/paper/2607.03171/) (2026)
- [A temporal graph dissimilarity measure capturing epidemic spreading behavior](https://mlsanity.com/paper/2610.16456/) (2026)

## Abstract (arXiv)

In most social and information systems the activity of agents generates rapidly evolving time-varying networks. The temporal variation in networks' connectivity patterns and the ongoing dynamic processes are usually coupled in ways that still challenge our mathematical or computational modelling. Here we analyse a mobile call dataset and find a simple statistical law that characterize the temporal evolution of users' egocentric networks. We encode this observation in a reinforcement process defining a time-varying network model that exhibits the emergence of strong and weak ties. We study the effect of time-varying and heterogeneous interactions on the classic rumour spreading model in both synthetic, and real-world networks. We observe that strong ties severely inhibit information diffusion by confining the spreading process among agents with recurrent communication patterns. This provides the counterintuitive evidence that strong ties may have a negative role in the spreading of information across networks.