assemblykor: Korean National Assembly Data for Political Science Education

Description

Provides ready-to-use datasets from the Korean National Assembly for teaching quantitative methods in political science. Includes five built-in datasets covering legislator metadata, bills, asset declarations, policy seminars, and committee speeches.

Built-in datasets

• legislators: 947 MP records (20th-22nd assemblies)

• bills: 60,925 legislative bills

• wealth: 2,928 legislator-year asset declarations

• seminars: 5,962 legislator-year seminar records

• speeches: 15,843 speech records (22nd, Science & ICT Committee)

• votes: 7,997 plenary vote tallies (20th-22nd assemblies)

• roll_calls: 368,210 member-level roll call votes (22nd assembly)

Download functions

• get_bill_texts: 60,925 bill propose-reason texts

• get_proposers: 769,773 co-sponsorship records

Tutorials

Nine Korean-language tutorials covering tidyverse, visualization, regression, panel data, text analysis, network analysis, roll call analysis, bill success, and speech patterns. Use list_tutorials to see all tutorials, and open_tutorial to copy them to your working directory.

Author(s)

Maintainer: Kyusik Yang kyusik.yang@nyu.edu

See Also

Useful links:

• https://kyusik-yang.github.io/assemblykor/

• https://github.com/kyusik-yang/assemblykor

• Report bugs at https://github.com/kyusik-yang/assemblykor/issues

Bills Proposed in the Korean National Assembly (20th-22nd)

Description

Metadata for 60,925 legislative bills proposed during the 20th through 22nd Korean National Assembly (2016-2026).

Usage

bills

Format

A data frame with 60,925 rows and 9 variables:

bill_id

Unique bill identifier from the National Assembly system

bill_no

Numeric bill number

assembly

Assembly number (20, 21, or 22)

bill_name

Full bill title in Korean

committee

Standing committee to which the bill was referred

propose_date

Date the bill was formally proposed

result

Legislative outcome in Korean. Common values include passed as-is, expired at term end, and incorporated into alternative bill. See table(bills$result) for all values.

proposer

Name of the lead (primary) proposer

proposer_id

MONA_CD of the lead proposer (links to legislators$member_id)

Details

The Korean National Assembly has seen a dramatic increase in bill proposals: the 21st Assembly produced 23,655 bills versus 21,594 in the 20th. Most bills expire at the end of the assembly term (term expiry); only about 5\

Use get_bill_texts() to download the full propose-reason texts for text analysis, and get_proposers() for the complete co-sponsorship records (769,773 rows).

Source

Open National Assembly Information API (Republic of Korea).

Examples

data(bills)

# Bills per assembly
table(bills$assembly)

# Top 10 committees
sort(table(bills$committee), decreasing = TRUE)[1:10]

# Distribution of legislative outcomes
head(sort(table(bills$result), decreasing = TRUE))

Download bill propose-reason texts

Description

Downloads the full propose-reason texts (jean-iyu) for all 60,925 bills. The file is approximately 40 MB and is cached locally after the first download. Requires the arrow package to read parquet files.

Usage

get_bill_texts(cache_dir = NULL, force_download = FALSE)

Arguments

Value

A data frame with 60,925 rows and 3 variables:

bill_id

Bill identifier (links to bills$bill_id)

propose_reason

Full text of the propose-reason statement (Korean)

scrape_status

Data collection status: "ok", "empty", "no_csrf", or "error"

Examples

texts <- get_bill_texts()
nchar_dist <- nchar(texts$propose_reason)
hist(nchar_dist, breaks = 100, main = "Length of Propose-Reason Texts")

Download bill co-sponsorship records

Description

Downloads the complete proposer records (769,773 rows) listing every legislator who co-sponsored each bill. Requires the arrow package.

Usage

get_proposers(cache_dir = NULL, force_download = FALSE)

Arguments

Value

A data frame with 769,773 rows and 8 variables:

bill_id

Bill identifier (links to bills$bill_id)

bill_no

Numeric bill number

bill_name

Bill title in Korean

propose_date

Proposal date

proposer_name

Legislator name

proposer_party

Party affiliation at the time of co-sponsorship

member_id

Legislator identifier (links to legislators$member_id)

is_lead

Logical: TRUE if lead (primary) proposer, FALSE if co-sponsor

Examples

props <- get_proposers()

# Build co-sponsorship edgelist
library(dplyr)
leads <- props %>% filter(is_lead) %>% select(bill_id, lead = member_id)
cosponsors <- props %>% filter(!is_lead) %>% select(bill_id, cosponsor = member_id)
edges <- inner_join(leads, cosponsors, by = "bill_id")

Members of the Korean National Assembly (20th-22nd)

Description

Biographical and political metadata for 947 records of legislators who served in the 20th (2016-2020), 21st (2020-2024), or 22nd (2024-2028) Korean National Assembly. Some legislators appear in multiple assemblies.

Usage

legislators

Format

A data frame with 947 rows and 15 variables:

member_id

Unique legislator identifier (MONA_CD from the National Assembly API)

assembly

Assembly number (20, 21, or 22)

name

Name in Korean (hangul)

name_hanja

Name in Chinese characters (hanja)

name_eng

Name in English (romanized)

party

Party affiliation during the assembly term

party_elected

Party at the time of election

district

Electoral district name, or party list position for proportional members

district_type

Election type: "constituency" or "proportional"

committees

Standing committee assignments (comma-separated)

gender

"M" (male) or "F" (female)

birth_date

Date of birth

seniority

Number of terms served, including current (1 = first-term)

n_bills

Total bills participated in (as lead proposer or co-sponsor)

n_bills_lead

Bills proposed as lead (primary) proposer

Details

661 unique legislators served across the three assemblies. member_id is consistent across assemblies, so legislators can be tracked over time. Party names may differ between party (mid-term) and party_elected (election day) due to party mergers and name changes, which are common in Korean politics.

Source

Open National Assembly Information API (Republic of Korea). License: public domain (Korean government open data).

Examples

data(legislators)

# Party composition by assembly
table(legislators$assembly, legislators$party)

# Gender gap in bill production
tapply(legislators$n_bills_lead, legislators$gender, median)

# First-term vs senior legislators
boxplot(n_bills_lead ~ seniority, data = legislators,
        xlab = "Terms served", ylab = "Bills proposed (lead)")

List available tutorials

Description

Lists the tutorial R Markdown files included with the package. Tutorials are designed for classroom use in Korean political science methods courses. Each tutorial is available in two formats:

1. Plain Rmd for editing in RStudio (open_tutorial)

2. Interactive learnr format (run_tutorial)

Usage

list_tutorials()

Value

A character vector of tutorial file names (invisibly).

Examples

list_tutorials()

Open a tutorial file

Description

Copies a tutorial R Markdown file to the specified directory (default: current working directory) so students can edit and run it in RStudio.

Usage

open_tutorial(name, dest_dir = getwd())

Arguments

Value

The path to the copied file (invisibly).

See Also

run_tutorial for the interactive browser version.

Examples

if (interactive()) {
  # Copy by name
  open_tutorial("01-tidyverse-basics")

  # Copy by number
  open_tutorial(1)
}

Path to assemblykor CSV files

Description

Returns the file path to CSV versions of the built-in datasets stored in inst/extdata. Useful for teaching file I/O with read.csv() or readr::read_csv().

Usage

path_to_file(file = NULL)

Arguments

Value

A character string with the full file path.

Examples

# Read data from CSV (alternative to data())
path <- path_to_file("legislators.csv")
legislators_csv <- read.csv(path, fileEncoding = "UTF-8")
head(legislators_csv)

Member-Level Roll Call Votes (22nd Assembly)

Description

Individual legislator voting records for all 1,233 bills that went to a recorded plenary vote in the 22nd Korean National Assembly (2024-2026). Each row represents one legislator's vote on one bill.

Usage

roll_calls

Format

A data frame with 368,210 rows and 8 variables:

bill_id

Bill identifier (links to votes$bill_id and bills$bill_id)

assembly

Assembly number (22)

member_name

Legislator name in Korean

member_id

Legislator identifier (MONA_CD, links to legislators$member_id)

party

Party affiliation at time of vote

district

Electoral district or proportional list position

vote

Vote cast in Korean: one of four values meaning yes, no, abstain, or absent

vote_date

Date of the vote

Details

The member-level roll call API is only available for the 22nd assembly. For the 20th and 21st assemblies, use the bill-level votes dataset.

This dataset enables ideal point estimation (e.g., W-NOMINATE), party unity scores, and analysis of legislative coalitions. Use member_id to link with legislators for biographical metadata.

Source

Open National Assembly Information API (Republic of Korea), endpoint nojepdqqaweusdfbi.

See Also

votes

Examples

data(roll_calls)

# Vote distribution
table(roll_calls$vote)

# Votes per party
head(sort(table(roll_calls$party), decreasing = TRUE))

# Number of unique legislators
length(unique(roll_calls$member_id))

Run an interactive tutorial

Description

Launches a learnr interactive tutorial in the browser. Students can type and run code directly in the browser with hints and solutions. Requires the learnr package.

Usage

run_tutorial(name)

Arguments

Value

No return value, called for the side effect of launching a learnr tutorial in the browser.

See Also

open_tutorial for the plain Rmd version.

Examples

if (interactive()) {
  run_tutorial(1)
}

Policy Seminar Activity by Legislator-Year (2000-2025)

Description

Annual panel of policy seminar hosting activity for legislators in the 16th through 22nd Korean National Assembly. Policy seminars (jeongchaek semina) are informal legislative events where MPs invite experts, stakeholders, and colleagues from other parties to discuss policy issues.

Usage

seminars

Format

A data frame with 5,962 rows and 18 variables:

name

Legislator name in Korean

member_id

Legislator identifier (MONA_CD, links to legislators$member_id). Available for ~95\ NA for unmatched or ambiguous (homonym) cases.

year

Calendar year

assembly

Assembly number (17-22)

party

Party affiliation

camp

Political camp: "liberal", "conservative", "progressive", or "other" (values are in Korean)

seniority

Number of terms served

n_seminars

Number of policy seminars hosted that year

n_cross_party

Number of seminars co-hosted with other-party legislators

cross_party_ratio

Share of seminars that were cross-party (0-1)

avg_coalition_size

Average number of co-hosts per seminar

is_governing

Logical: belongs to the governing (presidential) party

is_female

Logical: female legislator

is_proportional

Logical: proportional-representation member

is_seoul

Logical: represents a Seoul district

province

Province/metro area of electoral district

total_terms

Total assembly terms served across career

n_bills_led

Number of bills proposed as lead proposer that year

Details

Policy seminars are a distinctive feature of the Korean National Assembly. Unlike floor speeches or committee hearings, seminars are voluntary and allow legislators to signal policy expertise and build cross-party ties. The cross_party_ratio variable captures how often a legislator cooperates across party lines in this informal arena.

The is_governing variable enables difference-in-differences designs: when a party transitions from opposition to governing (or vice versa), does its members' cross-party collaboration change?

Source

National Assembly Seminar Database, collected via API.

Examples

data(seminars)

# Cross-party collaboration by governing status
tapply(seminars$cross_party_ratio, seminars$is_governing, mean, na.rm = TRUE)

# Seminar activity over time
agg <- aggregate(n_seminars ~ year, data = seminars, FUN = sum)
plot(agg, type = "b", main = "Total Policy Seminars by Year")

# Gender gap in seminar hosting
tapply(seminars$n_seminars, seminars$is_female, median, na.rm = TRUE)

Set Korean font for ggplot2

Description

Detects a Korean-compatible font on the current system and applies it to all ggplot2 plots via theme_set(). Call this once at the top of your script to avoid broken Korean text in plot titles and labels.

Usage

set_ko_font(font = NULL)

Arguments

Value

The font family name used (invisibly).

Examples

if (interactive()) {
  library(ggplot2)
  set_ko_font()

  # Now Korean text renders correctly
  ggplot(data.frame(x = 1), aes(x, x)) +
    geom_point() +
    labs(title = "Korean Title Test")
}

Committee Speeches from the Science and ICT Committee (22nd Assembly)

Description

Full corpus of 15,843 speech records from the Science, Technology, Information, Broadcasting and Communications Committee of the 22nd Korean National Assembly (2024). Standing committee meetings only.

Usage

speeches

Format

A data frame with 15,843 rows and 9 variables:

assembly

Assembly number (22)

date

Date of the committee meeting

committee

Committee name in Korean

speaker

Speaker label as it appears in the minutes (may include titles)

role

Speaker role: "legislator", "chair", "minister", "vice_minister", "senior_bureaucrat", "agency_head", "witness", "expert_witness", "nominee", "minister_nominee", "testifier", "public_corp_head", "broadcasting", "committee_staff"

speaker_name

Cleaned speaker name with titles removed

member_id

Legislator identifier (MONA_CD, links to legislators$member_id). Available for all rows; however, non-legislator speakers (ministers, witnesses, etc.) will not match entries in legislators.

speech_order

Order of the speech turn within the meeting

speech

Full text of the speech in Korean

Details

This dataset contains the complete standing committee speech records (no sampling) for the Science and ICT Committee of the 22nd assembly (June-December 2024). Speeches shorter than 50 characters were excluded.

The role variable distinguishes legislators from government officials, witnesses, and other participants. Filter to role == "legislator" for MP speeches only, or compare how legislators and ministers discuss the same agenda items.

This committee covers AI, telecommunications, broadcasting, space policy, and R&D governance, making it suitable for keyword analysis, topic modeling, and other text analysis exercises.

Source

National Assembly committee minutes via the Open National Assembly Information API.

Examples

data(speeches)

# Distribution of speech lengths
hist(nchar(speeches$speech), breaks = 100,
     main = "Speech Length Distribution", xlab = "Characters")

# Speaker roles
table(speeches$role)

# Most frequent legislator speakers
leg <- speeches[speeches$role == "legislator", ]
head(sort(table(leg$speaker_name), decreasing = TRUE), 10)

# Simple keyword search (example: AI-related speeches)
ai <- speeches[grepl("AI", speeches$speech), ]
nrow(ai)

Plenary Vote Results in the Korean National Assembly (20th-22nd)

Description

Bill-level vote tallies from plenary sessions of the 20th through 22nd Korean National Assembly (2016-2026). Each row represents one bill that went to a recorded floor vote.

Usage

votes

Format

A data frame with 7,997 rows and 13 variables:

bill_id

Unique bill identifier (links to bills$bill_id)

bill_no

Numeric bill number

bill_name

Full bill title in Korean

assembly

Assembly number (20, 21, or 22)

committee

Standing committee to which the bill was referred

vote_date

Date of the plenary vote

result

Vote outcome in Korean (e.g., passed as-is, passed with amendments, rejected)

bill_type

Type of bill (e.g., legislation, budget, resolution)

total_members

Total number of assembly members at the time

voted

Number of members who cast a vote

yes

Number of yes votes

no

Number of no votes

abstain

Number of abstentions

Details

Not all bills go to a floor vote. Most bills are disposed of in committee or expire at the end of the assembly term. The votes dataset captures only those that reached the plenary floor for a recorded vote.

About 40\ because bills only contains legislator-proposed bills while votes also includes committee alternatives, budget bills, and resolutions that have separate identifiers.

See roll_calls for member-level voting records (22nd assembly), useful for ideal point estimation or party discipline analysis.

Source

Open National Assembly Information API (Republic of Korea), endpoint ncocpgfiaoituanbr.

Examples

data(votes)

# Votes per assembly
table(votes$assembly)

# Pass rate
table(votes$result)

# Average yes rate
votes$yes_rate <- votes$yes / votes$voted
summary(votes$yes_rate)

# Contentious votes (yes rate < 70%)
contentious <- votes[votes$yes / votes$voted < 0.7, ]
nrow(contentious)

Legislator Asset Declarations (2015-2025)

Description

Panel data of asset declarations for 773 Korean National Assembly members across 13 reporting periods (2015-2025). Derived from mandatory public disclosures via the OpenWatch project.

Usage

wealth

Format

A data frame with 2,928 rows and 14 variables:

member_id

Legislator identifier (links to legislators$member_id)

year

Disclosure year (2015-2025)

name

Legislator name in Korean

total_assets

Total declared assets, in thousands of KRW

total_debt

Total declared liabilities, in thousands of KRW

net_worth

Net worth (assets minus debt), in thousands of KRW

real_estate

Total real estate value, in thousands of KRW

building

Total building/structure value, in thousands of KRW

land

Total land value, in thousands of KRW

deposits

Total bank deposits, in thousands of KRW

stocks

Total stock holdings, in thousands of KRW

n_properties

Total number of properties disclosed

has_seoul_property

Logical: owns property in Seoul

has_gangnam_property

Logical: owns property in Gangnam (Seoul's wealthiest district)

Details

All monetary values are in thousands of KRW (1 unit = 1,000 won). To convert to billions of won, divide by 1,000,000. For example, a net_worth of 1,670,000 means 1.67 billion won (approximately USD 1.2 million).

Legislators are required by law to disclose their assets annually. Not all legislators appear in every year, as the panel is unbalanced (entries correspond to active service periods).

Source

OpenWatch (https://docs.openwatch.kr/data/national-assembly), CC BY-SA 4.0 license.

Examples

data(wealth)

# Distribution of net worth (in billions of won)
hist(wealth$net_worth / 1e6, breaks = 50,
     main = "Legislator Net Worth", xlab = "Billion KRW")

# Real estate as share of total assets
wealth$re_share <- wealth$real_estate / wealth$total_assets
summary(wealth$re_share)

# Gangnam property owners vs others
tapply(wealth$net_worth / 1e6, wealth$has_gangnam_property, median, na.rm = TRUE)