38 lines
1.6 KiB
R
38 lines
1.6 KiB
R
library(dplyr)
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library(lubridate)
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library(rdd)
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library(stringr)
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contributing_count_data_filepath <- "/mmfs1/gscratch/comdata/users/mjilg/govdoc-cr-data/final_data/CONTRIBUTING_weekly_count_data.csv"
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contributing_count_df = read.csv(contributing_count_data_filepath, header = TRUE)
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contributing_topic_dist_filepath <- "text_analysis/020125_CONTRIBUTING_file_topic_distributions.csv"
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contributing_topics_df = read.csv(contributing_topic_dist_filepath, header = TRUE)
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window_num <- 5
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contributing_count_df <- contributing_count_df |>
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filter(week_index >= (- window_num) & week_index <= (window_num)) |>
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mutate(scaled_age = scale(age)) |>
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mutate(scaled_age_at_commit = scale(age_at_commit))|>
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mutate(log1p_count = log1p(commit_count))
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summed_data <- contributing_count_df |>
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filter(before_after == 1) |>
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group_by(project_id) |>
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summarise_at(vars(commit_count), list(summed_count=sum))
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contributing_topics_df <- contributing_topics_df |>
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mutate(project_id = sapply(str_split(filename, "_hullabaloo_"), `[`, 1)) |>
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mutate(project_id = ifelse(filename=="_vcr_vcr_CONTRIBUTING.md", "vcr_vcr", project_id)) |>
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mutate(project_id = ifelse(filename=="marshmallow-code_marshmallow.git_CONTRIBUTING.rst", "marshmallow-code_marshmallow.git", project_id))
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merged_df <- inner_join(summed_data, contributing_topics_df, by="project_id")
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merged_df$logged_commits <- log1p(merged_df$summed_count)
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library(MASS)
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commit_outcome_model <- glm.nb(logged_commits ~ 0 + t0 + t1 + t2 + t3 + t4, data=merged_df)
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qqnorm(residuals(commit_outcome_model))
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summary(commit_outcome_model)
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saveRDS(commit_outcome_model, "020325_commit_topic_model.rda")
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