summary.dynet: Describe a temporal network

In Dynet: Tidy Temporal Network Analysis

Describe a temporal network

Description

A tidy description of the whole network, one row per property. Two densities are reported and they answer different questions. Snapshot density is the mean over time bins of realised against possible edges. Temporal density is the proportion of all possible relational exposure occupied during the observation window. Overlapping and duplicate spells for the same ordered pair, or dyad in an undirected network, are unioned before their duration is counted.

Usage

## S3 method for class 'dynet'
summary(object, temporal_density = FALSE, ...)

Arguments

object	A temporal network from dynet().
temporal_density	Whether to compute the temporal-density row. FALSE, the default, reports "not computed" for it. The quantity integrates exact occupancy over every eligible ordered pair, so its cost grows with the square of the vertex count: on a 442-vertex forum network it takes about 32 seconds, while every other row in the table is immediate. Pass TRUE when the number is wanted.
...	Ignored.

Details

Let Y_q(t) indicate that both endpoints of relational opportunity q are eligible at positive observed time t, and let E_q(t) indicate binary union edge activity. Temporal density is

\rho = \frac{\sum_q \int Y_q(t)E_q(t)dt} {\sum_q \int Y_q(t)dt}.

Directed opportunities are ordered; undirected opportunities are unordered. The integrals are evaluated exactly over observation, vertex, and edge change points. Self-loops, weights, session labels, duplicate spells, genuine points, and observation gaps do not add exposure. A network with no positive time containing two coeligible distinct vertices has undefined temporal density and reports NA.

This is an occupancy definition. Unlike summing spell durations, it remains in ⁠[0, 1]⁠ when the same relation has overlapping or duplicated spells.

Value

A data.frame with columns property and value, one row per property.

References

Bender-deMoll, S., & Morris, M. (2025). tsna: Tools for Temporal Social Network Analysis. R package version 0.3.6.

Holme, P., & Saramaki, J. (2012). Temporal networks. Physics Reports, 519(3), 97-125.

Latapy, M., Viard, T., & Magnien, C. (2018). Stream graphs and link streams for the modeling of interactions over time. Social Network Analysis and Mining, 8, 61.

Examples

dn <- dynet(school_contacts)
summary(dn)

# The temporal density is opt-in, since it is quadratic in the vertex count.
summary(dn, temporal_density = TRUE)

Dynet documentation built on Oct. 7, 2026, 5:08 p.m.