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/**
* @module Intelligence/Terminology
* @category Intelligence Operations / Supporting Infrastructure
* @name Vocabulary Extraction - Political Terminology Pattern Analysis
*
* @description
* Advanced terminology extraction system analyzing translated news articles across
* all 14 supported languages to identify and catalog political terminology patterns.
* Supports intelligence operatives in understanding how political concepts translate
* across linguistic and cultural contexts.
*
* Core Mission:
* Automatic extraction of political terminology from published news articles,
* enabling vocabulary enrichment across 14 language variants. Identifies key political
* terms, party names, committee references, legislative concepts, and institutional
* terminology used in Riksdag coverage. Supports linguistic analysis for translation
* quality assurance and political concept comparison across Nordic/European contexts.
*
* Supported Languages (14):
* - Latin Scripts: English (en), Swedish (sv), Danish (da), Norwegian (no), Finnish (fi),
* German (de), French (fr), Spanish (es), Dutch (nl)
* - Non-Latin Scripts: Arabic (ar - RTL), Hebrew (he - RTL),
* Japanese (ja - Kanji/Hiragana/Katakana), Korean (ko - Hangul), Chinese (zh - Hanzi)
*
* Terminology Categories Extracted:
* - Political titles and roles (e.g., "Riksdagsledamot", "Statsminister", "Minister")
* - Committee references (e.g., "Försvarsutskottet", "Finansutskottet")
* - Party mentions and abbreviations (S, M, SD, V, MP, C, L, KD)
* - Legislative terms (propositioner, motioner, betänkanden, skrivelser)
* - Institutional acronyms (EU, NATO, UN, etc.)
* - Policy domains (försvar, miljö, ekonomi, välfärd)
*
* Extraction Methodology:
* - Structure-based extraction using HTML element analysis (language-agnostic)
* - Parses article titles (h3 elements) as primary terminology source
* - Extracts "What to Watch" and key context headings
* - Handles "Why This Matters" explanatory sections
* - Cross-references historical context and related articles
* - Supports all character encodings (UTF-8 with proper multi-byte handling)
*
* Technical Architecture:
* - CLI-configurable date filtering for temporal analysis
* - Comprehensive error reporting with file-level granularity
* - Support for all Unicode scripts (Latin, CJK, Arabic/Hebrew bidirectional)
* - Handles HTML entity encoding and special character sequences
* - Generates JSON output for downstream linguistic analysis
*
* Intelligence Applications:
* - Terminology pattern analysis for translation consistency
* - Identification of emerging political concepts and terminology
* - Cross-language comparison of political discourse
* - Support for cultural intelligence analysis
* - Input to automated translation quality assurance
* - Political terminology reference for analyst briefings
*
* Data Processing Pipeline:
* - Scans news/ directory for published articles
* - Filters by date range (--from-date, --to-date parameters)
* - Extracts terminology from HTML structure
* - Deduplicates and normalizes extracted terms
* - Generates comprehensive terminology report
* - Logs skipped files and processing errors
*
* Output Format:
* JSON file containing:
* - titles: Array of extracted h3 titles (primary terminology)
* - headings: Array of h2 section headings
* - whyMatters: Content from "Why This Matters" sections
* - context: Historical context and reference sections
* - metadata: Extraction statistics and processing info
*
* Usage:
* node scripts/extract-vocabulary.js
* node scripts/extract-vocabulary.js --from-date=2026-01-01 --to-date=2026-02-01
* node scripts/extract-vocabulary.js --lang=sv
*
* Integration Points:
* - Consumed by automated translation quality assurance systems
* - Used in terminology glossary maintenance workflows
* - Feeds political concept mapping for intelligence dashboards
* - Referenced in editorial consistency validation
*
* GDPR & Data Protection:
* - Processes only published, public articles
* - Extracts terminology only (no personal identifiers)
* - Complies with GDPR Article 5 (transparency)
* - No storage of personal data in terminology output
* - Audit trail of extraction dates and processing
*
* Linguistic Considerations:
* - Preserves non-Latin character scripts exactly as published
* - Handles right-to-left languages (Arabic, Hebrew) properly
* - Supports CJK character analysis without segmentation
* - Respects linguistic conventions for each language
*
* @intelligence Core tool for political terminology analysis across languages
* @osint Analyzes published public government documents and articles
* @risk Incomplete terminology extraction may omit emerging political concepts
* @gdpr No personal data extraction (terminology/concepts only)
* @security File access restricted to article directory; no system-wide scanning
*
* @author Hack23 AB (Linguistic Intelligence Team)
* @license Apache-2.0
* @version 2.5.0
* @see extract-vocabulary.js (this file)
* @see political terminology references for each language
* @see Unicode Standard for multi-script support
* @see GDPR Article 5 - Principles relating to processing
*/
import { readFileSync, readdirSync } from 'fs';
import { basename, join } from 'path';
const LANGUAGES = {
en: 'English', sv: 'Swedish', da: 'Danish', no: 'Norwegian', fi: 'Finnish',
de: 'German', fr: 'French', es: 'Spanish', nl: 'Dutch',
ar: 'Arabic', he: 'Hebrew', ja: 'Japanese', ko: 'Korean', zh: 'Chinese'
};
// Track skipped files for warning summary
const skippedFiles = [];
/**
* Extract political terms from HTML content using structure-based approach
*/
function extractTerms(content, lang) {
const terms = {};
// Extract titles (main political terminology)
// Handle both plain text and <span> wrapped titles
const h3Pattern = /<h3>(.*?)<\/h3>/g;
const h3Matches = [];
let h3Match;
while ((h3Match = h3Pattern.exec(content)) !== null) {
// Strip any inner tags (like <span>) to get clean text
const cleanText = h3Match[1].replace(/<[^>]+>/g, '').trim();
if (cleanText) h3Matches.push(cleanText);
}
terms.titles = h3Matches.slice(0, 10);
// Extract "What to Watch" heading (any language) - structure-based
const h2Pattern = /<h2[^>]*>([^<]+)<\/h2>/g;
const h2Matches = [];
let h2Match;
while ((h2Match = h2Pattern.exec(content)) !== null) {
const text = h2Match[1].trim();
// Heuristic: "What to Watch" headings often contain these keywords
if (text.length > 5 && text.length < 100) {
h2Matches.push(text);
}
}
if (h2Matches.length > 0) {
// Assume first h2 is "What to Watch" if present
terms.watchLabel = h2Matches[0];
}
// Extract structured labels from <strong>…:</strong> (language-agnostic)
const strongLabelPattern = /<strong>\s*([^:<]+?)\s*:\s*<\/strong>/g;
const strongLabels = [];
let strongMatch;
while ((strongMatch = strongLabelPattern.exec(content)) !== null) {
const label = strongMatch[1].trim();
if (label.length > 0 && label.length < 50) {
strongLabels.push(label);
}
}
// Convention: first label is often committee, second is document
if (strongLabels[0]) terms.committeeLabel = strongLabels[0];
if (strongLabels[1]) terms.documentLabel = strongLabels[1];
// Extract article type from title
const titleMatch = content.match(/<h1>([^<]+)<\/h1>/);
if (titleMatch) terms.mainTitle = titleMatch[1].trim();
return terms;
}
/**
* Analyze all news articles
*/
function analyzeArticles(directory = 'news', datePrefix = null) {
const results = {};
for (const lang of Object.keys(LANGUAGES)) {
results[lang] = {
language: LANGUAGES[lang],
code: lang,
samples: []
};
}
try {
const files = readdirSync(directory).filter(f => {
if (!f.endsWith('.html')) return false;
if (datePrefix && !f.includes(datePrefix)) return false;
return true;
});
console.log(`\nScanning ${files.length} HTML files in ${directory}/`);
if (datePrefix) {
console.log(`Filtering by date prefix: "${datePrefix}"\n`);
}
for (const file of files) {
const match = file.match(/-([a-z]{2})\.html$/);
if (!match) {
skippedFiles.push({ file, reason: 'No language code in filename' });
continue;
}
const lang = match[1];
if (!results[lang]) {
skippedFiles.push({ file, reason: `Unknown language code: ${lang}` });
continue;
}
try {
const content = readFileSync(join(directory, file), 'utf-8');
const terms = extractTerms(content, lang);
// Determine article type
let articleType = 'general';
if (file.includes('committee')) articleType = 'committee-reports';
else if (file.includes('proposition')) articleType = 'propositions';
else if (file.includes('motion')) articleType = 'motions';
else if (file.includes('evening')) articleType = 'evening-analysis';
else if (file.includes('week-ahead')) articleType = 'week-ahead';
results[lang].samples.push({
file: basename(file),
type: articleType,
terms
});
} catch (error) {
skippedFiles.push({ file, reason: `Read error: ${error.message}` });
}
}
} catch (error) {
console.error(`Error reading directory: ${error.message}`);
process.exit(1);
}
return results;
}
/**
* Generate vocabulary report
*/
function generateReport(results) {
console.log('\n========================================');
console.log('Political Vocabulary Analysis Report');
console.log('========================================\n');
for (const [code, data] of Object.entries(results)) {
if (data.samples.length === 0) continue;
console.log(`\n## ${data.language} (${code.toUpperCase()})`);
console.log(`Samples analyzed: ${data.samples.length}`);
// Collect unique labels
const watchLabels = new Set();
const committeeLabels = new Set();
const documentLabels = new Set();
const mainTitles = new Set();
for (const sample of data.samples) {
if (sample.terms.watchLabel) watchLabels.add(sample.terms.watchLabel);
if (sample.terms.committeeLabel) committeeLabels.add(sample.terms.committeeLabel);
if (sample.terms.documentLabel) documentLabels.add(sample.terms.documentLabel);
if (sample.terms.mainTitle) mainTitles.add(sample.terms.mainTitle);
}
if (watchLabels.size > 0) console.log(` "What to Watch": ${Array.from(watchLabels).join(', ')}`);
if (committeeLabels.size > 0) console.log(` "Committee": ${Array.from(committeeLabels).join(', ')}`);
if (documentLabels.size > 0) console.log(` "Document": ${Array.from(documentLabels).join(', ')}`);
// Show sample titles from any articles (prioritize committee reports)
const committeeReports = data.samples.filter(s => s.type === 'committee-reports');
const sampleWithTitles = committeeReports.find(s => s.terms.titles && s.terms.titles.length > 0) ||
data.samples.find(s => s.terms.titles && s.terms.titles.length > 0);
if (sampleWithTitles && sampleWithTitles.terms.titles.length > 0) {
console.log(` Sample titles: ${sampleWithTitles.terms.titles.slice(0, 3).join(', ')}`);
}
}
// Warning summary
if (skippedFiles.length > 0) {
console.log('\n\n⚠️ WARNING: Skipped Files Summary');
console.log('=====================================');
console.log(`Total skipped: ${skippedFiles.length}\n`);
// Group by reason
const byReason = {};
for (const { file, reason } of skippedFiles) {
if (!byReason[reason]) byReason[reason] = [];
byReason[reason].push(file);
}
for (const [reason, files] of Object.entries(byReason)) {
console.log(`${reason}: ${files.length} file(s)`);
if (files.length <= 5) {
files.forEach(f => console.log(` - ${f}`));
} else {
files.slice(0, 3).forEach(f => console.log(` - ${f}`));
console.log(` ... and ${files.length - 3} more`);
}
console.log();
}
}
console.log('\n========================================');
console.log('Analysis complete!');
console.log('========================================\n');
}
// Parse CLI arguments
const args = process.argv.slice(2);
let datePrefix = null;
let directory = 'news';
for (let i = 0; i < args.length; i++) {
if (args[i] === '--date-prefix' && args[i + 1]) {
datePrefix = args[i + 1];
i++;
} else if (args[i] === '--directory' && args[i + 1]) {
directory = args[i + 1];
i++;
} else if (args[i] === '--help' || args[i] === '-h') {
console.log(`
Usage: node scripts/extract-vocabulary.js [options]
Options:
--date-prefix <prefix> Filter files by date prefix (e.g., "2026-02-")
--directory <path> Directory to scan (default: "news")
--help, -h Show this help message
Examples:
node scripts/extract-vocabulary.js
node scripts/extract-vocabulary.js --date-prefix 2026-02-
node scripts/extract-vocabulary.js --directory news --date-prefix 2026-03-
`);
process.exit(0);
}
}
// Run analysis
const results = analyzeArticles(directory, datePrefix);
generateReport(results);
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