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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?

Structural user roles

Each node is assigned one of six interpretable roles per period:

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

Example use cases

Online learning communities — Who becomes isolated? Are discussions clique-based?
Social media platforms — Is recommendation driving unequal visibility?
Workplace collaboration — Are teams siloing after a reorg?
Educational peer networks — Do minority students become more peripheral over time?

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()`

Citation

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

License

GPL-3 (c) Subir Hait

These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
Health stats visible at Monitor.