Armin
180 lines
8.8 KiB
R
180 lines
8.8 KiB
R
# ============================================================
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# process_manifesto.R - Manifesto Project Data Processing
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# ============================================================
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# Processes Manifesto Project data for the two-dimensional party-position model
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# Input: $PARTY2D_RAW_DATA_DIR/manifesto/MPDataset_MPDS2025a.csv
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# Output: manifesto_data.csv
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# ============================================================
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library(tidyverse)
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library(countrycode)
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library(purrr)
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# Set working directory (works both in RStudio and command line)
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if (interactive() && requireNamespace("rstudioapi", quietly = TRUE)) {
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try(setwd(dirname(rstudioapi::getActiveDocumentContext()$path)), silent = TRUE)
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}
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cat("Processing Manifesto Project data...\n")
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raw_data_dir <- Sys.getenv(
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"PARTY2D_RAW_DATA_DIR",
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unset = file.path("..", "..", "_local", "raw")
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)
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manifesto_raw_path <- file.path(raw_data_dir, "manifesto", "MPDataset_MPDS2025a.csv")
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partyfacts_path <- file.path(raw_data_dir, "partyfacts", "partyfacts-external-parties.csv")
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# ============================================================
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# PartyFacts Linkage
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# ============================================================
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partyfacts_raw <- read_csv(partyfacts_path, show_col_types = FALSE)
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manifesto_link <- partyfacts_raw %>%
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filter(dataset_key == "manifesto") %>%
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transmute(id = dataset_party_id,
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country = countrycode(country, origin = 'iso3c', destination = "iso2c"),
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party = partyfacts_id,
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party = ifelse(party == 622, 604, party))
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# ============================================================
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# Load Manifesto Data
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# ============================================================
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manifesto_data <- read_csv(manifesto_raw_path, show_col_types = FALSE)
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# ============================================================
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# CMP Code Mapping to 4 Dimensions
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# ============================================================
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vars <- tribble(
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~type, ~subtype, ~per_var, ~stance, ~label,
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# pro_market
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"pro_market", "Market Regulation", "per401", "Positive", "Free Market Economy",
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"pro_market", "Economic Liberalization","per402", "Positive", "Incentives: Positive",
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"pro_market", "Market Regulation", "per407", "Positive", "Protectionism: Negative",
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"pro_market", "Economic Liberalization","per414", "Positive", "Economic Orthodoxy",
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"pro_market", "Economic Liberalization","per505", "Positive", "Welfare State Limitation",
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"pro_market", "Economic Liberalization","per507", "Positive", "Education Limitation",
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"pro_market", "Economic Liberalization","per702", "Positive", "Labour Groups: Negative",
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"pro_market", "Market Regulation", "per406", "Negative", "Protectionism: Positive",
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"pro_market", "Market Regulation", "per412", "Negative", "Controlled Economy",
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"pro_market", "Economic Liberalization","per504", "Negative", "Welfare State Expansion",
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# pro_welfare
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"pro_welfare", "Economic Intervention", "per403", "Positive", "Market Regulation",
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"pro_welfare", "Economic Intervention", "per404", "Positive", "Economic Planning",
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"pro_welfare", "Economic Intervention", "per412", "Positive", "Controlled Economy",
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"pro_welfare", "Economic Intervention", "per413", "Positive", "Nationalisation",
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"pro_welfare", "Social Services", "per504", "Positive", "Welfare State Expansion",
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"pro_welfare", "Social Services", "per506", "Positive", "Education Expansion",
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"pro_welfare", "Economic Intervention", "per701", "Positive", "Labour Groups: Positive",
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"pro_welfare", "Economic Intervention", "per401", "Negative", "Free Market Economy",
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"pro_welfare", "Social Services", "per505", "Negative", "Welfare State Limitation",
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# cosmopolitan
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"cosmopolitan", "Internationalism", "per107", "Positive", "Internationalism: Positive",
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"cosmopolitan", "Internationalism", "per108", "Positive", "European Community/Union: Positive",
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"cosmopolitan", "Multiculturalism", "per607", "Positive", "Multiculturalism: Positive",
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"cosmopolitan", "Multiculturalism", "per201", "Positive", "Freedom and Human Rights",
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"cosmopolitan", "Multiculturalism", "per604", "Positive", "traditional Morality: Negative",
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"cosmopolitan", "Internationalism", "per109", "Negative", "Internationalism: Negative",
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"cosmopolitan", "Multiculturalism", "per601", "Negative", "National Way of Life: Positive",
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# traditional
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"traditional", "National Identity", "per109", "Positive", "Internationalism: Negative",
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"traditional", "Conservative Morality", "per110", "Positive", "European Community/Union: Negative",
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"traditional", "National Identity", "per601", "Positive", "National Way of Life: Positive",
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"traditional", "Conservative Morality", "per603", "Positive", "traditional Morality: Positive",
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"traditional", "Conservative Morality", "per608", "Positive", "Multiculturalism: Negative",
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"traditional", "Conservative Morality", "per605", "Positive", "Law and Order: Positive",
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"traditional", "National Identity", "per107", "Negative", "Internationalism: Positive",
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"traditional", "Conservative Morality", "per607", "Negative", "Multiculturalism: Positive"
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)
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# ============================================================
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# Process Manifesto Data
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# ============================================================
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manifesto <- vars %>%
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pmap_dfr(~ manifesto_data %>%
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transmute(country = countrycode(countryname, origin = 'country.name', destination = 'iso2c'),
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year = as.numeric(format(as.Date(edate, format = "%d/%m/%Y"), "%Y")),
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id = as.character(party),
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count = round(.data[[..3]]),
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var = ..3,
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label = ..5,
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type = ..1,
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subtype = ..2,
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stance = ..4,
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project = 'Manifesto Project') %>%
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left_join(manifesto_link, by = c("id", "country")) %>%
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select(-id)) %>%
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group_by(party, country, year, subtype) %>%
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summarise(
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positive = sum(count[stance == "Positive"], na.rm = TRUE),
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sample = sum(count, na.rm = TRUE),
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type = first(type),
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project = first(project),
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.groups = "drop"
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) %>%
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na.omit() %>%
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rename(var = subtype) %>%
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# Convert to bipolar bridge structure (type_high/type_low)
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mutate(
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type_high = case_when(
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type == "pro_welfare" ~ "pro_welfare",
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type == "pro_market" ~ "pro_market",
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type == "cosmopolitan" ~ "cosmopolitan",
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type == "traditional" ~ "traditional"
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),
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type_low = case_when(
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type %in% c("pro_welfare", "pro_market") ~ ifelse(type == "pro_welfare", "pro_market", "pro_welfare"),
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type %in% c("cosmopolitan", "traditional") ~ ifelse(type == "cosmopolitan", "traditional", "cosmopolitan")
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)
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) %>%
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select(-type) %>%
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# Add _manifesto suffix to variable names
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mutate(var = paste0(tolower(gsub(" ", "_", var)), "_manifesto"))
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# ============================================================
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# NOTE: Temporal continuity filter moved to the data setup orchestrator.
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# This allows exempting parties that appear in parliamentary data
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# (parties in parliament are by definition not fringe parties)
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# ============================================================
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cat("Skipping temporal filter (applied in 02_build_model_inputs.R after combining with other text data)\n")
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cat(sprintf(" Parties: %d\n", n_distinct(manifesto$party)))
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# ============================================================
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# Write Output
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# ============================================================
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write_csv(manifesto, "manifesto_data.csv")
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cat(sprintf("Output: manifesto_data.csv (%d rows, %d parties)\n",
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nrow(manifesto), n_distinct(manifesto$party)))
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# ============================================================
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# Election Data Extraction (vote shares)
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# ============================================================
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cat("\nExtracting election data (pervote)...\n")
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election_data <- manifesto_data %>%
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transmute(
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country = countrycode(countryname, origin = 'country.name', destination = 'iso2c'),
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year = as.numeric(format(as.Date(edate, format = "%d/%m/%Y"), "%Y")),
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id = as.character(party),
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pervote = pervote
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) %>%
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left_join(manifesto_link, by = c("id", "country")) %>%
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select(-id) %>%
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filter(!is.na(party), !is.na(pervote)) %>%
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# Keep one row per (party, country, year) — take max pervote if duplicates
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group_by(party, country, year) %>%
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summarise(pervote = max(pervote, na.rm = TRUE), .groups = "drop") %>%
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arrange(country, party, year)
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write_csv(election_data, "election_data.csv")
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cat(sprintf("Output: election_data.csv (%d rows, %d parties)\n",
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nrow(election_data), n_distinct(election_data$party)))
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# Export manifesto_link for use by other scripts
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# (poldem also needs it for CMP linkage)
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