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A long-format heterogeneous sequence dataset built from Nestimate::human_long and Nestimate::ai_long by collapsing several near-synonym codes into a smaller, more interpretable alphabet. Suitable as a teaching example for build_htna().

Usage

human_ai

Format

A data frame with 19347 rows and 11 columns:

message_id

Integer. Source message identifier.

project

Character. Project label (e.g. "Project_1").

session_id

Character. Session identifier — pass to build_htna() as the session key.

timestamp

Integer. Unix timestamp of the message.

session_date

Character. Date of the session (YYYY-MM-DD).

code

Character. Simplified action code; the code-column value passed to build_htna().

cluster

Character. Original cluster label from the source data, retained for reference (see Details).

code_order

Integer. Order of the code within the message.

order_in_session

Integer. Order of the row within the session — pass as the order key to build_htna().

actor_type

Character. "AI" or "Human" — the actor partition for build_htna(actor_type = "actor_type").

phase

Factor with levels "Early" and "Late". Session-level cohort tag from a chronological split: sessions ordered by their first session_date (with session_id as a deterministic tiebreak), then split in half. Suitable for build_htna(group = "phase").

Source

Derived from Nestimate::human_long and Nestimate::ai_long; see data-raw/human_ai.R for the build script.

Details

Code remapping (all other codes pass through unchanged):

  • AI: Investigate, Ask, Inquire \(\to\) Ask; Explain, Report \(\to\) Report.

  • Human: Command, Request \(\to\) Request; Correct, Verify \(\to\) Check; Interrupt, Frustrate \(\to\) Frustrate.

Resulting alphabets:

  • AI (6): Ask, Delegate, Execute, Plan, Repair, Report.

  • Human (6): Check, Frustrate, Inquire, Refine, Request, Specify.

Because two source codes can map to the same simplified code while originally belonging to different cluster values, a single simplified code may appear with more than one cluster label across rows. The cluster column is preserved verbatim from the source data and should be treated as informational only.

Examples

# \donttest{
data(human_ai)
net <- build_htna(human_ai, actor_type = "actor_type")
#> Warning: A network with one long sequence is not recommended and can't be validated using bootstrap and other confirmatory testings.
#> Metadata aggregated per session: ties resolved by first occurrence in 'session_date' (1 sessions), 'cluster' (42 sessions), 'actor_type' (24 sessions)
plot_htna(net)

# }