78 lines
3.0 KiB
R
Executable File
78 lines
3.0 KiB
R
Executable File
#!/usr/bin/env Rscript
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# Top level script for building datasets.
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# Copyright (C) 2018 Nathan TeBlunthuis
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# This program is free software: you can redistribute it and/or modify
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# it under the terms of the GNU General Public License as published by
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# the Free Software Foundation, either version 3 of the License, or
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# (at your option) any later version.
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# This program is distributed in the hope that it will be useful,
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# but WITHOUT ANY WARRANTY; without even the implied warranty of
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# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
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# GNU General Public License for more details.
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# You should have received a copy of the GNU General Public License
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# along with this program. If not, see <https://www.gnu.org/licenses/>.
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library(data.table)
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library(parallel)
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plot.distribution <- function(data,varname,save=TRUE){
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x = data[[varname]];
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print(paste("plotting distribution for",varname))
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if(save){
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pdf(paste0("plots/",varname,".distribution.pdf"))
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}
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## overlay histogram, empirical density and normal density
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if(class(x) == "logical"){
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p0 <- qplot(x)
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}
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else{
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p0 = qplot(x, geom = 'blank') +
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geom_line(aes(y = ..density.., colour = 'Empirical'), stat = 'density') +
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geom_histogram(aes(y = ..density..), alpha = 0.4,bins=100) +
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scale_colour_manual(name = 'Density', values = c('red', 'blue')) +
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theme(legend.position = c(0.85, 0.85))
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}
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print(p0)
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if(save){
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dev.off()
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}
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}
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if(!exists("wiki.list")){
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source("lib-00-utils.R",echo=TRUE)
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}
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if(!exists("bots") | !exists("admins")){
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if(file.exists("bots.RDS") & file.exists("admins.RDS")){
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bots = readRDS("bots.RDS")
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admins = readRDS("admins.RDS")
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}
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else {
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source("lib-01-generate_userroles.R",echo=TRUE)
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}
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}
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if(!exists("newcomer.dt")){
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intermediate.files <- list("newcomers.RDS","wikiweeks.RDS","wiki.stats.RDS","active.editors.RDS")
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if(! all(sapply(intermediate.files,function (x) file.exists(x)))){
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source("lib-01-build_newcomer_table.R",echo=TRUE)
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}
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}
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plot.distributions = FALSE
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if(plot.distributions == TRUE){
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library(ggplot2)
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## plot distributions for model 1
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outcome1 <- c("survives")
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predictors1 <- c("is.reverted","is.messaged","is.bot.reverted","is.reverted.messaged","is.admin.reverted","BRD.initiation","BRD.reciprocation")
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controls1 <- c("ns0.edits","ns1.edits","ns4.edits","n.other.wikis","week","has.edited.other.wikis","n.edits.other","n.messages","n.editors","total.wiki.length","revert.rate","revert.disc.rate","newcomer.revert.disc.rate","revert.message.rate","newcomer.revert.message.rate","newcomer.edits.rate","bot.revert.rate","bot.revert.prop","newcomer.bot.revert.rate","newcomer.bot.revert.prop","admin.revert.rate","admin.revert.prop","n.ns4.edits","n.ns4.editors","d.ns4.length","ns4.editor.age","age","wiki.age")
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for(varname in c(outcome1,predictors1,controls1)){
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plot.distribution(newcomers,varname)
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}
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}
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