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mw-lifecycle-analysis/121325_work/misc.R
2025-12-15 20:37:59 -08:00

73 lines
2.5 KiB
R

library(tidyverse)
library(dplyr)
library(lubridate)
c1_event_date <- as.Date("2013-07-01")
c2_event_date <- as.Date("2013-08-28")
c3_event_date <- as.Date("2015-07-02")
relative_week <- function(date, ref_date) {
as.integer(as.numeric(difftime(date, ref_date, units = "days")) %/% 7)
}
core_csv <-"~/121325_work/121225_vd_data/extension_VisualEditor_2000-01-01_to_2016-12-31.csv"
core_df <- read.csv(core_csv, header = TRUE)
known_affil_emails <- c("krinkle@fastmail.com", "roan.kattouw@gmail.com",
"trevorparscal@gmail.com", "krinklemail@gmail.com", "moriel@gmail.com")
active_names<- c("Timo Tijhof", "Krinkle", "Roan Kattouw", "Catrope",
"Trevor Parscal", "Ed Sanders")
core_df <- core_df |>
mutate(commit_date = ymd_hms(commit_date)) |>
mutate(isAuthorWMF = case_when(
author_name %in% active_names ~ "FIVE",
grepl("@wikimedia\\.org", author_email, ignore.case = TRUE) ~ "TRUE",
grepl("@wikimedia\\.de", author_email, ignore.case = TRUE) ~ "TRUE",
grepl("l10n-bot@translatewiki\\.net", author_email, ignore.case = TRUE) ~ "localization",
grepl("@gerrit\\.wikimedia\\.org", author_email, ignore.case = TRUE) ~ "Gerrit",
TRUE ~ "FALSE"
)) |>
mutate(isVE = case_when(
grepl("VisualEditor", message, ignore.case = TRUE) ~ TRUE,
grepl(" VE ", message, ignore.case = TRUE) ~ TRUE,
TRUE ~ FALSE
))
c1_core_weekly <- core_df |>
mutate(week_index = relative_week(commit_date, c1_event_date)) |>
group_by(week_index, isAuthorWMF)|>
summarise(count = n(), .groups = 'drop')|>
filter(week_index >= -9 & week_index < -4) |>
mutate(source = 'c1')
c1summary <- c1_core_weekly |>
group_by(isAuthorWMF)|>
summarize(total = sum(count))
c2_core_weekly <- core_df |>
mutate(week_index = relative_week(commit_date, c2_event_date)) |>
group_by(week_index, isAuthorWMF)|>
summarise(count = n(), .groups = 'drop')|>
filter(week_index >= -104 & week_index <= 13) |>
mutate(source = 'c2')
c3_core_weekly <- core_df |>
mutate(week_index = relative_week(commit_date, c3_event_date)) |>
group_by(week_index, isAuthorWMF)|>
summarise(count = n(), .groups = 'drop')|>
filter(week_index >= -83 & week_index <= 13) |>
mutate(source = 'c3')
#collate and save
core_weekly <- rbind(c1_core_weekly, c2_core_weekly, c3_core_weekly)
c1summary <- c1_core_weekly |>
group_by(isAuthorWMF)|>
summarize(total = sum(count))
c2summary <- c2_core_weekly |>
group_by(isAuthorWMF)|>
summarize(total = sum(count))
c3summary <- c3_core_weekly |>
group_by(isAuthorWMF)|>
summarize(total = sum(count))