updating case studies for comparative analysis
29
.sh_history
@ -122,3 +122,32 @@ cd final_data
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ls
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cd metadata
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ls
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cd ..cd dkdsjlksdfjlkjlksdfjlkfsdjlklll
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cd ..
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ls
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cd ..
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ls
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cd . .
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cd ..
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ls
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cd mw-repo-lifecycles
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ls
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ls case3
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ls
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cd ..
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ls
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cd case4
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cd case3
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ls
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mkdir 043025-stale-data
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mv event_0415_mediawiki_core_weekly_commit_count_data.csv 043025-stale-data/
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mv event_0422_mediawiki_core_weekly_count.csv 043025-stale-data/
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ls
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cd ..
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ls
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cd case1`
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cd case1
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lds
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ls
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cd ../case2
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ls
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|
Before Width: | Height: | Size: 1.5 MiB |
Before Width: | Height: | Size: 1.4 MiB |
Before Width: | Height: | Size: 734 KiB |
@ -5,7 +5,7 @@ library(tidyr)
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library(purrr)
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library(stringr)
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https_commit_fp <- "/mmfs1/gscratch/comdata/users/mjilg/mw-repo-lifecycles/case1/extensions_visualeditor_commits.csv"
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https_commit_fp <- "/mmfs1/gscratch/comdata/users/mjilg/mw-repo-lifecycles/case2/mediawiki_core_commits.csv"
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contains_http_but_not_url <- function(text) {
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if (is.na(text)) {
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@ -28,7 +28,7 @@ contains_http_but_not_url <- function(text) {
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if (str_detect(word, "tls")){
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return(TRUE)
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}
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if (startsWith(word, "cert")){
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if (startsWith(word, "cert") && !startsWith(word, "certain")){
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return(TRUE)
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}
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}
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@ -207,7 +207,7 @@ transform_relevant_commit_data <- function(filepath){
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# TODO: this is project/event specific
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event_date <- as.Date("2015-07-02")
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event_date <- as.Date("2013-08-28")
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#event_date <- as.Date("2013-07-01")
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#event_date <- as.Date("2013-04-25")
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#event_date <- as.Date("2012-12-11")
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@ -231,13 +231,13 @@ transform_relevant_commit_data <- function(filepath){
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#drop out data from ''before'' the release process
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df <- df |>
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filter(commit_date >= as.Date("2015-04-01"))
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filter(commit_date >= as.Date("2011-09-03"))
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#we are looking at weekly data, 6m before and 6m after
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#start_date <- event_date %m-% months(6)
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calculated_start_date <- event_date %m-% months(12)
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start_date <- max(calculated_start_date, oldest_commit_date)
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end_date <- event_date %m+% months(12)
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#calculated_start_date <- event_date %m-% months(12)
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start_date <- as.Date('2011-09-03')
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end_date <-as.Date('2013-11-27')
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#getting the relative weeks to the publication date
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relative_week <- function(date, ref_date) {
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@ -260,7 +260,7 @@ transform_relevant_commit_data <- function(filepath){
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# list all author_emails with >5 commits
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# for big df: if author not in the list, 'new' author
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old_author_list <- df |>
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filter(commit_date < as.Date("2015-06-01"))|>
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filter(commit_date > as.Date("2011-09-03") & commit_date < as.Date("2013-08-01"))|>
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group_by(author_email) |>
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summarise(commit_count = n()) |>
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filter(commit_count > 5) |>
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@ -357,14 +357,14 @@ transform_relevant_commit_data <- function(filepath){
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# ) |>
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weekly_commits <- weekly_commits |>
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filter(relative_week >= (-14) & relative_week <= 52 )
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filter(relative_week >= (-103) & relative_week <= 13 )
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#gracefully exit
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return(weekly_commits)
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}
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transformed <- transform_commit_data(https_commit_fp)
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output_filepath <-"/mmfs1/gscratch/comdata/users/mjilg/mw-repo-lifecycles/case1/event_0421_extensions_ve_weekly_count.csv"
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transformed <- transform_relevant_commit_data(https_commit_fp)
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output_filepath <-"/mmfs1/gscratch/comdata/users/mjilg/mw-repo-lifecycles/case2/event_0430_mediawiki_core_weekly_count.csv"
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write.csv(transformed, output_filepath, row.names = FALSE)
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@ -1,5 +1,5 @@
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library(tidyverse)
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count_data_fp <-"/mmfs1/gscratch/comdata/users/mjilg/mw-repo-lifecycles/case1/event_0421_extensions_ve_weekly_count.csv"
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count_data_fp <-"/mmfs1/gscratch/comdata/users/mjilg/mw-repo-lifecycles/case2/event_0430_mediawiki_core_weekly_count.csv"
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input_df <- read.csv(count_data_fp, header = TRUE)
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input_df$nonbot_commit_count <- input_df$commit_count - input_df$bot_commit_count
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@ -9,31 +9,29 @@ library(scales)
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library(ggplot2)
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long_df <- input_df |>
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tidyr::pivot_longer(cols = c(nonbot_commit_count, unaff_commit_count, wikimedia_commit_count),
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tidyr::pivot_longer(cols = c(unaff_commit_count, wikimedia_commit_count),
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names_to = "commit_type",
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values_to = "lengthened_commit_count")
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affiliationColors <-
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setNames( c('black','#5da2d8', '#c7756a')
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,c("nonbot_commit_count","unaff_commit_count", "wikimedia_commit_count"))
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setNames( c('#5da2d8', '#c7756a')
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,c("unaff_commit_count", "wikimedia_commit_count"))
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commit_authors <- long_df |>
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ggplot(aes(x=relative_week,
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y=lengthened_commit_count,
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color=factor(commit_type))) +
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geom_point() +
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geom_line() +
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labs(x = "Relative Week", y = "Commits", color="Commit Type") +
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scale_color_manual(values = affiliationColors,
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labels = c("nonbot_commit_count" = "Total Nonbot Commits",
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"unaff_commit_count" = "Unaffiliated Commits",
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fill=factor(commit_type))) +
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geom_col(position='dodge') +
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labs(x = "Relative Week", y = "Commits", fill="Commit Type") +
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scale_fill_manual(values = affiliationColors,
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labels = c("unaff_commit_count" = "Unaffiliated Commits",
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"wikimedia_commit_count" = "WMF Commits")) +
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ggtitle("Total VE Commits Around Opt-out Deployment By Affiliation") +
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ggtitle("Total Relevant Core Commits Around HTTPS-as-default Deployment") +
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theme_bw() +
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theme(legend.position = "top")
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commit_authors
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ggsave(filename = "0421-ve-commits.png", plot = commit_authors, width = 12, height = 9, dpi = 800)
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ggsave(filename = "ww-c2-0430-commits.png", plot = commit_authors, width = 12, height = 9, dpi = 800)
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# new affiliation things
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@ -52,23 +50,21 @@ new_authors_long_df <- input_df |>
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new_unaff_authors <- new_authors_long_df |>
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ggplot(aes(x=relative_week,
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y=lengthened_commit_count,
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linetype=commit_seniority)) +
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geom_point(color = '#5da2d8') +
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geom_line(color='#5da2d8') +
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labs(x = "Relative Week", y = "Commits", linetype="Commit Seniority ('New' contributors <= 5 commits before 06-06-2013)") +
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scale_linetype_manual(
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values = c("returning_unaff_commit_count" = "solid",
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"unaff_new_commit_count" = "dotted"),
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fill=commit_seniority)) +
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geom_col(color = '#5da2d8', position='dodge') +
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labs(x = "Relative Week", y = "Commits", fill="Commit Seniority ('New' contributors <= 5 commits before 06-06-2013)") +
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scale_fill_manual(values = c("returning_unaff_commit_count" = "#FFC107", # Color for "Returning Contributors"
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"unaff_new_commit_count" = "#004D40"),
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labels = c("returning_unaff_commit_count" = "Returning Contributors",
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"unaff_new_commit_count" = "New Contributors")
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) +
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ggtitle("Unaffiliated VE Commits Surrounding Opt-out Deployment") +
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ggtitle("Unaffiliated Relevant Core Commits Around HTTPS-as-default Deployment") +
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theme_bw() +
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theme(legend.position = "top")
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new_unaff_authors
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ggsave(filename = "0421-ve-spike-commits.png", plot = new_unaff_authors, width = 12, height = 9, dpi = 800)
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ggsave(filename = "ww-c2-0430-unaff-commit-spike.png", plot = new_unaff_authors, width = 12, height = 9, dpi = 800)
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new_authors <- long_df |>
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ggplot(aes(x=relative_week,
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|
206
commit_analysis/relevance-plot.R
Normal file
@ -0,0 +1,206 @@
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#library(tidyverse)
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library(dplyr)
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library(lubridate)
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library(tidyr)
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library(purrr)
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library(stringr)
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https_commit_fp <- "/mmfs1/gscratch/comdata/users/mjilg/mw-repo-lifecycles/case2/mediawiki_core_commits.csv"
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contains_http_but_not_url <- function(text) {
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if (is.na(text)) {
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return(FALSE)
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}
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# Split text by whitespace and check each word
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words <- str_split(text, "\\s+")[[1]]
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for (word in words) {
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if (!str_detect(word,"://")){
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#http
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if (str_detect(word, "http")){
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return(TRUE)
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}
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if (str_detect(word, "login")){
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return(TRUE)
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}
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if (str_detect(word, "ssl")){
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return(TRUE)
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}
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if (str_detect(word, "tls")){
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return(TRUE)
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}
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if (startsWith(word, "cert") && !startsWith(word, "certain")){
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return(TRUE)
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}
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}
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}
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return(FALSE)
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}
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transform_relevant_commit_data <- function(filepath){
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#basic, loading in the file
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df = read.csv(filepath, header = TRUE)
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temp_df <- df
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dir_path = dirname(filepath)
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file_name = basename(filepath)
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# TODO: this is project/event specific
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event_date <- as.Date("2013-08-28")
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#event_date <- as.Date("2013-07-01")
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#event_date <- as.Date("2013-04-25")
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#event_date <- as.Date("2012-12-11")
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# isolate project id
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project_id <- sub("_.*$", "", file_name)
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#make sure the dates are formatted correctly and state the project_id
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df <- df |>
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mutate(commit_date = ymd_hms(commit_date)) |>
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mutate(project_id = project_id)
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#get information about project age either in the "present"
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#or at the time of first commit
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oldest_commit_date <- min(as.Date(df$commit_date))
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project_age <- as.numeric(as.Date("2025-02-10") - oldest_commit_date)
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#add that to the data
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df <- df |>
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mutate(age = project_age)
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#drop out data from ''before'' the release process
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df <- df |>
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filter(commit_date >= as.Date("2011-09-03"))
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#we are looking at weekly data, 6m before and 6m after
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#start_date <- event_date %m-% months(6)
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#calculated_start_date <- event_date %m-% months(12)
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start_date <- as.Date('2011-09-03')
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end_date <-as.Date('2015-10-03')
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#getting the relative weeks to the publication date
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relative_week <- function(date, ref_date) {
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as.integer(as.numeric(difftime(date, ref_date, units = "days")) %/% 7)
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}
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df <- df |>
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mutate(relative_week = relative_week(commit_date, event_date))|>
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mutate(mentions_http = if_else(sapply(message, contains_http_but_not_url), TRUE, FALSE))
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# arrange(relative_week) |>
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# group_by(author_email) |>
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# mutate(new_author = ifelse(row_number() <= 5, 1, 0),
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# new_author_wmf = if_else(grepl("@wikimedia", author_email), new_author, 0),
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# new_author_unaff = if_else(!grepl("@wikimedia", author_email), new_author, 0)) |>
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# ungroup()
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# cut the df to all before 06-01-2015
|
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# group by author_email
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# list all author_emails with >5 commits
|
||||
# for big df: if author not in the list, 'new' author
|
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old_author_list <- df |>
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||||
filter(commit_date > as.Date("2011-09-03") & commit_date < as.Date("2013-08-01"))|>
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||||
group_by(author_email) |>
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summarise(commit_count = n()) |>
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||||
filter(commit_count > 5) |>
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||||
pull(author_email)
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||||
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||||
# Label authors as 'new' if they are not in the old_author_list
|
||||
df <- df |>
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||||
mutate(new_author = ifelse(author_email %in% old_author_list, 0, 1),
|
||||
new_author_wmf = if_else(grepl("@wikimedia", author_email),
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||||
new_author, 0),
|
||||
new_author_unaff = if_else(!grepl("@wikimedia", author_email) &
|
||||
!grepl("l10n-bot@translatewiki.net|tools.libraryupgrader@tools.wmflabs.org", author_email),
|
||||
new_author, 0))
|
||||
|
||||
|
||||
#filler for when there are weeks without commits
|
||||
all_weeks <- seq(relative_week(start_date, event_date), relative_week(end_date, event_date))
|
||||
complete_weeks_df <- expand.grid(relative_week = all_weeks,
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||||
project_id = project_id,
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||||
age = project_age)
|
||||
|
||||
|
||||
#for each week, get the list of unique authors that committed
|
||||
#cumulative_authors <- df %>%
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||||
# arrange(relative_week) %>%
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||||
# group_by(relative_week) %>%
|
||||
# summarize(cumulative_author_emails = list(unique(author_email)), .groups = 'drop')
|
||||
#same for each committer
|
||||
#cumulative_committers <- df %>%
|
||||
# arrange(relative_week) %>%
|
||||
# group_by(relative_week) %>%
|
||||
# summarize(cumulative_committer_emails = list(unique(committer_email)), .groups = 'drop')
|
||||
|
||||
#now cut out the commit data that we don't care about
|
||||
df <- df |>
|
||||
filter(author_email != "jenkins-bot@gerrit.wikimedia.org") |>
|
||||
filter(author_email != "l10n-bot@translatewiki.net") |>
|
||||
filter(author_email != "tools.libraryupgrader@tools.wmflabs.org")
|
||||
|
||||
#in order:
|
||||
# - we group by project, week, ages
|
||||
# - and we summarize commit and authorship details
|
||||
# - we then fill in information for missingness
|
||||
# - and add in vars for before/after
|
||||
# - and weekly index
|
||||
weekly_commits <- df |>
|
||||
group_by(project_id, relative_week, age) |>
|
||||
summarise(commit_count = n(),
|
||||
author_emails = list(unique(author_email)),
|
||||
committer_emails = list(unique(committer_email)),
|
||||
mediawiki_dev_commit_count = sum(grepl("@users.mediawiki.org", author_email)),
|
||||
wikimedia_commit_count = sum(grepl("@wikimedia", author_email)),
|
||||
wikia_commit_count = sum(grepl("@wikia-inc.com", author_email)),
|
||||
bot_commit_count = sum(grepl("l10n-bot@translatewiki.net|tools.libraryupgrader@tools.wmflabs.org", author_email)),
|
||||
wmf_new_commit_count = sum(new_author_wmf),
|
||||
unaff_new_commit_count = sum(new_author_unaff),
|
||||
relevant_commits = sum(mentions_http),
|
||||
.groups = 'drop') |>
|
||||
right_join(complete_weeks_df, by=c("relative_week", "project_id", "age")) |>
|
||||
replace_na(list(commit_count = 0)) |>
|
||||
replace_na(list(wikimedia_commit_count = 0)) |>
|
||||
replace_na(list(l10n_commit_count = 0)) |>
|
||||
replace_na(list(jenkins_commit_count = 0)) |>
|
||||
replace_na(list(mediawiki_dev_commit_count = 0)) |>
|
||||
replace_na(list(wikia_commit_count = 0)) |>
|
||||
replace_na(list(bot_commit_count = 0)) |>
|
||||
replace_na(list(wmf_new_commit_count = 0)) |>
|
||||
replace_na(list(unaff_new_commit_count = 0)) |>
|
||||
replace_na(list(relevant_commits = 0)) |>
|
||||
mutate(before_after = if_else(relative_week < 0, 0, 1)) |>
|
||||
select(-author_emails, -committer_emails)
|
||||
|
||||
weekly_commits <- weekly_commits |>
|
||||
filter(relative_week >= (-103) & relative_week <= 109 )
|
||||
|
||||
#gracefully exit
|
||||
return(weekly_commits)
|
||||
}
|
||||
|
||||
transformed <- transform_relevant_commit_data(https_commit_fp)
|
||||
|
||||
transformed$irrelevant_commit = transformed$commit_count - transformed$relevant_commits
|
||||
|
||||
long_df <- transformed|>
|
||||
tidyr::pivot_longer(cols = c(irrelevant_commit, relevant_commits),
|
||||
names_to = "commit_relevance",
|
||||
values_to = "lengthened_commit_count")
|
||||
|
||||
relevant_https_commits <- long_df |>
|
||||
ggplot(aes(x=relative_week,
|
||||
y=lengthened_commit_count,
|
||||
fill=commit_relevance)) +
|
||||
geom_col(position = "dodge", width = 0.7) +
|
||||
labs(x = "Relative Week", y = "Commits", fill="Commit relevance") +
|
||||
scale_fill_manual(values = c("irrelevant_commit" = "#E1BE6A", # Color for "Returning Contributors"
|
||||
"relevant_commits" = "#40B0A6"),
|
||||
labels = c("irrelevant_commit" = "Irrelevant Commits",
|
||||
"relevant_commits" = "Relevant Commits")
|
||||
) +
|
||||
ggtitle("Commits to MW-Core, 09-03-2011 to 10-03-2015, by relevance to HTTP/s feature deployments") +
|
||||
theme_bw() +
|
||||
theme(legend.position = "top")
|
||||
|
||||
relevant_https_commits
|
||||
|
||||
ggsave(filename = "ww-c2c3-relevance-viz.png", plot = relevant_https_commits, width = 12, height = 9, dpi = 800)
|
@ -1,17 +0,0 @@
|
||||
1. SSH tunnel from your workstation using the following command:
|
||||
|
||||
ssh -N -L 8787:n3439:46227 mjilg@klone.hyak.uw.edu
|
||||
|
||||
and point your web browser to http://localhost:8787
|
||||
|
||||
2. log in to RStudio Server using the following credentials:
|
||||
|
||||
user: mjilg
|
||||
password: AJ9ua2VJPYQLsa6g6Fbq
|
||||
|
||||
When done using RStudio Server, terminate the job by:
|
||||
|
||||
1. Exit the RStudio Session ("power" button in the top right corner of the RStudio window)
|
||||
2. Issue the following command on the login node:
|
||||
|
||||
scancel -f 25494157
|
BIN
ww-c2c3-relevance-viz.png
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ww-figures/ww-c1-0430-commits.png
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ww-figures/ww-c1-0430-unaff-commit-spike.png
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After Width: | Height: | Size: 420 KiB |
BIN
ww-figures/ww-c2-0430-commits.png
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After Width: | Height: | Size: 372 KiB |
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ww-figures/ww-c2-0430-unaff-commit-spike.png
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BIN
ww-figures/ww-c3-0430-commits.png
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After Width: | Height: | Size: 370 KiB |
BIN
ww-figures/ww-c3-0430-unaff-commit-spike.png
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After Width: | Height: | Size: 406 KiB |