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govdoc-cr-analysis/topic-outcome-models/contributing_topic_outcome_model.R
2025-02-07 16:59:56 -08:00

38 lines
1.5 KiB
R

library(dplyr)
library(lubridate)
library(rdd)
library(stringr)
contributing_count_data_filepath <- "/mmfs1/gscratch/comdata/users/mjilg/govdoc-cr-data/final_data/metadata/final_0207_CONTRIBUTING_weekly_count_data.csv"
contributing_count_df = read.csv(contributing_count_data_filepath, header = TRUE)
contributing_topic_dist_filepath <- "text_analysis/020725_CONTRIBUTING_file_topic_distributions.csv"
contributing_topics_df = read.csv(contributing_topic_dist_filepath, header = TRUE)
contributing_merged_manifest <- "text_analysis/0207_contributing_merged_manifest.csv"
contributing_manifest_df <- read.csv(contributing_merged_manifest, header=TRUE)
merged_df <- inner_join(contributing_manifest_df, contributing_topics_df, by=c("new_filepath"= "filename"))
window_num <- 5
contributing_count_df <- contributing_count_df |>
filter(relative_week >= (- window_num) & relative_week <= (window_num)) |>
mutate(scaled_age = scale(age)) |>
mutate(scaled_age_at_commit = scale(age_at_commit))|>
mutate(log1p_count = log1p(commit_count))
summed_data <- contributing_count_df |>
filter(before_after == 1) |>
group_by(project_id) |>
summarise_at(vars(commit_count), list(summed_count=sum))
merged_df <- inner_join(summed_data, merged_df, by=c("project_id" = "repo_id"))
merged_df$logged_commits <- log1p(merged_df$summed_count)
library(MASS)
commit_outcome_model <- glm.nb(logged_commits ~ 0 + t0 + t1 + t2 + t3 + t4, data=merged_df)
qqnorm(residuals(commit_outcome_model))
summary(commit_outcome_model)
saveRDS(commit_outcome_model, "020725_commit_topic_model.rda")