mixing: Mixing between vertex groups over time

In Dynet: Tidy Temporal Network Analysis

Mixing between vertex groups over time

Description

How much each kind of vertex interacted with each other kind, in every time bin. This is the question a temporal network answers that a static one cannot: not whether high and low achievers mixed, but when they did, and whether the pattern held or decayed.

The grouping variable comes from the vertex attributes supplied to dynet() through its nodes argument.

Usage

mixing(
  dn,
  attribute,
  sessions = c("bounded", "collapse", "separate"),
  sample = NULL,
  start = NULL,
  end = NULL,
  step = NULL,
  window = NULL,
  plot = FALSE
)

Arguments

dn	A temporal network from dynet() built with vertex attributes.
attribute	Name of a column in the vertex table. A name the network does not carry raises an error of class dynet_unknown_attribute that lists the attributes it does have.
sessions	How to treat sessions, as in centrality_series(): "bounded" (the default), "collapse" or "separate". "separate" needs a network built with a session column and raises dynet_no_sessions otherwise.
sample	Deprecated. "instant" is equivalent to window = 0; "window" uses the current positive/default window.
start, end	First and last time at which to measure. Default to the observed range. A network built from dates may be addressed with dates.
step	How often to measure. Defaults to the interval the network was built with.
window	How much time each measurement covers. Defaults to step, which tiles the period into disjoint bins. A larger value slides an overlapping window; 0 samples the network at each point in time. "all" measures the whole observed period as one window, closed on the right so an event at the final instant is inside it; it cannot be combined with step, and under sessions = "separate" or discontinuous observation it gives one window per session or observed component.
plot	Whether to draw the result as well as return it. Drawing is a side effect in the manner of graphics::hist(): the verb still returns its tidy table, invisibly when it has drawn, so plot = TRUE saves the wrapping plot() call without changing what comes back. Use plot() on the result when the figure needs arguments of its own.

Details

Each cell is a raw count of distinct active binary vertex dyads. Repeated, overlapping, or split spells and edge weights do not multiply a dyad. Retained self-loops count once. For directed networks, every ordered group pair is reported and

M_{ab}=\sum_{u:g(u)=a}\sum_{v:g(v)=b}Y_{uv}.

The row and column margins are grouped outdegree and indegree, and the table sum is the active directed edge count including retained loops.

Undirected networks report one lexicographically canonical cell for each unordered group pair, with display labels such as "A -- B". A within-group edge or loop contributes once to its diagonal cell. The group stub margin is

d_a=2M_{aa}+\sum_{b\ne a}M_{\min(a,b),\max(a,b)},

so the margins sum to twice the table total. These are unnormalised counts, not Newman's mixing proportions.

Missing attribute values are retained as a collision-safe explicit group ordered after observed labels. Bounded and collapsed modes both use the binary calendar union: a dyad active in two sessions at the same time counts once. Separate mode returns session-local tables over the fixed group universe. Every supported cell is emitted, including zeros. Declared vertex activity first induces the endpoint-valid snapshot. The complete group-cell universe remains fixed, but inactive vertices and eligible isolates contribute no dyad.

Value

A dynet_metric at graph level with one row per time point and group pair. The columns are session (only under sessions = "separate", the one mode that keeps session labels apart), time, measure, value, from_group and to_group. Directed measure labels use "A -> B"; undirected labels use "A -- B". value is the active binary-dyad count, and the authoritative from_group and to_group columns identify the cell. Attributes record unit, pair-domain, normalisation, weight, loop, missing-group, and session-aggregation conventions.

Conditions

Errors: dynet_unknown_attribute (no such vertex attribute), dynet_no_sessions (sessions = "separate" without a session column), dynet_outside_observation (the requested range misses observed support; it also carries dynet_bad_input), and dynet_bad_input for every other broken contract – dn not a dynet, an attribute that is not a single column name, and an out-of-range start, end, step or window.

Warning: dynet_deprecated for the retired sample argument.

References

Newman, M. E. J. (2003). Mixing patterns in networks. Physical Review E, 67, 026126. \Sexpr[results=rd]{tools:::Rd_expr_doi("10.1103/PhysRevE.67.026126")}

Morris, M., Handcock, M. S., & Hunter, D. R. (2008). Specification of exponential-family random graph models: terms and computational aspects. Journal of Statistical Software, 24(4). \Sexpr[results=rd]{tools:::Rd_expr_doi("10.18637/jss.v024.i04")}

Examples

dn <- dynet(forum_posts, thread = "thread", nodes = forum_people)
role_mixing <- mixing(dn, attribute = "role")
role_mixing
plot(role_mixing)

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