New (non-founding) authors first appearing per repo-month, by source and popularity stratum

Community-expansion analogue of author_density_tbl(): rather than "how many distinct authors are active this month", counts how many people are showing up in a repository's issue tracker for the first time ever - a direct measure of whether a repo's community of interlocutors is still growing, or has stalled to the same recurring faces. Each repo's very first-ever issue author (typically the maintainer opening the repo's own first issue) is excluded as a "founding" event rather than a new arrival, since it isn't itself community growth. As with issue_rate_tbl()/author_density_tbl(), the result is normalised by repo-months of exposure and reported as a window-month trailing sum, so a single burst of new signups doesn't read as a permanent step change.

Usage

new_author_rate_tbl(
  issue_authors_tbl,
  repo_tbl,
  source_name,
  n_strata = 4L,
  window = 12L,
  date_start = as.Date("2015-01-01"),
  date_end = NULL
)

Arguments

issue_authors_tbl: As returned by fetch_issue_authors().
repo_tbl: As returned by build_repo_tbl().
source_name: One of repo_tbl$source ("pypi", "npm", "joss", "ropensci").
n_strata: Number of popularity strata.
window: Trailing aggregation window, in months. Default 12: each reported month's n_metric/n_repo_months sum that month and the preceding 11.
date_start, date_end: Date bounds on the analysis window; date_end defaults to the start of the current month.

Value

A tibble with one row per (popularity stratum, month): popularity_stratum, month, n_metric (trailing sum of new, non-founding first-time authors), n_repo_months, rate. Carries metric = "issues", window, and source_name as attributes (no contrib_threshold, since none applies here) so plot_activity()/ plot_new_author_rate() don't need to be told them again.

Details

Author identity here isn't split by contribution/contrib_threshold as most of this package's other rate tables are - someone who goes on to become a heavy contributor is still a new arrival the month they first show up, so every first-time author counts, core and non-core alike, matching solo_repo_share_tbl()'s treatment of contribution rather than issue_rate_tbl()'s.

Examples

if (FALSE) { # \dontrun{
na <- new_author_rate_tbl (issue_authors_tbl, repo_tbl, "pypi")
plot_activity (na) + ggplot2::labs (y = "New (non-founding) authors")
} # }