README

socialdrift

socialdrift is an R package for building, auditing, and visualising temporal social interaction networks from raw event-log data.

Most existing tools start after the graph already exists. socialdrift takes you from a table of raw platform events (follows, replies, mentions, likes) all the way through to longitudinal diagnostics, community health reports, and inequality audits.

Installation

# Install from GitHub (development version)
# install.packages("remotes")
remotes::install_github("causalfragility-lab/socialdrift")

Workflow at a glance

library(socialdrift)

# 1. Standardise event data
ev <- as_social_events(sim_social_events,
                       actor_group  = "actor_group",
                       target_group = "target_group")

# 2. Build monthly graph snapshots
gs <- build_graph_series(ev, window = "month")

# 3. Structural metrics
summarize_network_series(gs)

# 4. Network Drift Index
ndi <- network_drift(gs)
plot_network_drift(ndi)

# 5. Community dynamics
comm <- detect_communities_ts(gs)
community_fragmentation_index(comm)

# 6. User role trajectories
roles <- role_trajectories(gs)
plot_role_trajectories(roles)

# 7. Group disparity audit
audit_group_disparities(ev, gs)

Signature indices

Index	Function	Description
NDI	`network_drift()`	How much did overall network structure change?
CFI	`community_fragmentation_index()`	Are communities becoming more siloed?
VCI	`visibility_concentration_index()`	Is attention concentrating on fewer actors?
RMI	`role_mobility_index()`	How often do users transition between roles?

NDI

network_drift()

How much did overall network structure change?

CFI

community_fragmentation_index()

Are communities becoming more siloed?

VCI

visibility_concentration_index()

Is attention concentrating on fewer actors?

RMI

role_mobility_index()

How often do users transition between roles?

Structural user roles

Role	Description
`isolated`	No connections in this period
`peripheral`	Low degree, not a bridge
`broadcaster`	High out-degree, low in-degree
`popular`	High in-degree, low out-degree
`core`	High in- and out-degree
`bridge`	High betweenness centrality

isolated

No connections in this period

peripheral

Low degree, not a bridge

broadcaster

High out-degree, low in-degree

popular

High in-degree, low out-degree

core

High in- and out-degree

bridge

High betweenness centrality

Example use cases

Package modules

Module	Key functions
Data engineering	`as_social_events()`, `build_graph_series()`
Structural metrics	`network_density_ts()`, `reciprocity_ts()`, `clustering_ts()`, `degree_inequality_ts()`
Community dynamics	`detect_communities_ts()`, `community_drift()`, `community_fragmentation_index()`
Role trajectories	`classify_user_roles()`, `role_trajectories()`, `role_mobility_index()`
Drift & inequality	`network_drift()`, `visibility_concentration_index()`, `audit_group_disparities()`
Plotting	`plot_network_metrics()`, `plot_network_drift()`, `plot_role_trajectories()`

Data engineering

as_social_events(), build_graph_series()

Structural metrics

network_density_ts(), reciprocity_ts(), clustering_ts(), degree_inequality_ts()

Community dynamics

detect_communities_ts(), community_drift(), community_fragmentation_index()

Role trajectories

classify_user_roles(), role_trajectories(), role_mobility_index()

Drift & inequality

network_drift(), visibility_concentration_index(), audit_group_disparities()

Plotting

plot_network_metrics(), plot_network_drift(), plot_role_trajectories()

Citation

@Manual{socialdrift,
  title  = {socialdrift: Temporal Auditing of Social Interaction Networks},
  author = {Subir Hait},
  year   = {2025},
  note   = {R package version 0.1.0},
}