tsna {tsna}R Documentation

Tools for Temporal Social Network Analysis

Description

Temporal SNA tools for continuous- and discrete-time longitudinal networks. having vertex, edge, and attribute dynamics stored in the networkDynamic format. This work was supported by grant R01HD68395 from the National Institute of Health.

Details

This package provides tools for working with longitudinal network data in networkDynamic-package format. This data structure is essentially a list in the network format in which elements also have an attached activity.attribute, a matrix of spells indicating when vertex or edge is active. The networkDynamic package provides tools (networkDynamic) for translating longitudinal data from various formats (timed edge lists, lists of toggles, sets of matrices, etc).

Currently the package consists of several groups of functions

The sections below provide some additional details. The package vignette (browseVignettes(package='tsna')) gives additional examples and illustrations of key concepts.

It is the intention that, like the networkDynamic package, tsna should support both continuous time and discrete time representations of networks. However, we are prioritizing development of discrete time measures suitable for use with simulation data (i.e. stergm models) so many of the functions are still missing the necessary arguments to facilitate binning.

Standard 'static' Sna metrics

These functions operate by collapsing the dynamic network into a static network at a series of regular intervals and returning the results as a time series ts object. They can provide general description of trends in a network dataset. Generally assumes that vertex set is not substantially changing.

Temporal path based metrics

These functions compute and use temporal paths (network geodesics that are constrained by the activity times of edges) through a network.

Rates and Duration

These functions can be used to compute distributions of (observed) activity durations in a data structure. Note that due to censoring (edges that begin before or end after the time observation window for the network) the observed durations may be biased away from the 'real' values (or model parameters). The duration estimate functions use various types of survival analysis to return estimates of these values.

tsna Utilities

Data Sets

Source

This package is part of the statnet suite of packages http://statnet.org. For citation information see citation('tsna').


[Package tsna version 0.3.5 Index]