Source-linked AI summary
The dynamical strength of social ties in information spreading
Giovanna Miritello, Esteban Moro, Rubén Lara
TL;DR
The paper examines how bursty, group-based communication affects information spreading, addressing models that overlook temporal communication patterns. Using mobile-phone communication sequences, it defines dynamical tie strength and shows that conversations favor local cascades while bursts hinder reach at larger scales.
Problem
Most social-network spreading studies use static topologies and neglect temporal patterns, despite communication occurring in bursts and group conversations.
Method
The authors analyze mobile communication sequences, simulate SIR spreading against shuffled data, and map temporal transmission onto static percolation using dynamical tie strength.
Results
Real communication produces larger cascades than shuffled data at small propagation probability but narrower reach at large propagation probability, because conversations and bursts have opposing effects.
Takeaways & Limitations
Temporal communication patterns should be incorporated into social-network models, with dynamical tie strength providing an effective static representation of human interaction dynamics.
Abstract
from arXiv · showhide
We investigate the temporal patterns of human communication and its influence on the spreading of information in social networks. The analysis of mobile phone calls of 20 million people in one country shows that human communication is bursty and happens in group conversations. These features have opposite effects in information reach: while bursts hinder propagation at large scales, conversations favor local rapid cascades. To explain these phenomena we define the dynamical strength of social ties, a quantity that encompasses both the topological and temporal patterns of human communication.