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// SPDX-License-Identifier: Apache-2.0
/**
* @module Generators/Builders/VotingBuilders
* @description Deep analysis, SWOT, dashboard, mindmap and multi-dimensional SWOT
* builders for voting-based articles (motions, weekly/monthly review).
*/
import type {
DeepAnalysis,
StakeholderOutcome,
ActionConsequence,
PoliticalMistake,
VotingRecord,
VotingPattern,
VotingAnomaly,
MotionsQuestion,
LanguageCode,
SwotAnalysis,
DashboardConfig,
SwotBuilderStrings,
DashboardBuilderStrings,
IntelligenceMindmap,
MindmapNode,
ActorNode,
PolicyConnection,
StakeholderPerspective,
CoalitionMetrics,
MultiDimensionalSwot,
TemporalSwotAssessment,
StakeholderType,
VotingIntensity,
PolarizationIndex,
DashboardPanel,
} from '../../types/index.js';
import {
getLocalizedString,
SWOT_BUILDER_STRINGS,
DASHBOARD_BUILDER_STRINGS,
} from '../../constants/languages.js';
import { PLACEHOLDER_MARKER } from '../motions-content.js';
import {
buildDefaultStakeholderPerspectives,
computeVotingIntensity,
computePolarizationIndex,
} from '../../utils/intelligence-analysis.js';
import { AI_MARKER } from '../../constants/analysis-constants.js';
import {
buildOutcomeMatrix,
buildAiMarkerImpactAssessment,
buildCoalitionMetricsFromPatterns,
buildStakeholderMetricsFromVoting,
buildStakeholderPanel,
makeDimension,
EP_BLUE_TRANSPARENT,
EP_BLUE_BORDER,
CIVIL_SOCIETY,
} from './shared-builders.js';
/**
* Derive stakeholder outcomes from voting records.
* Groups with high cohesion (>0.8) and high participation (>0.7) are treated as
* "winners"; groups with low cohesion (<0.5) are flagged as "at risk".
* Returns `{actor, outcome, reason}` where `reason` is set to `AI_MARKER`
* so the AI enrichment step provides substantive political reasoning.
*
* @param records - Voting records
* @param patterns - Voting pattern data
* @returns Stakeholder outcome assessments with `reason` set to `AI_MARKER`
*/
function deriveStakeholderOutcomesFromVoting(
records: readonly VotingRecord[],
patterns: readonly VotingPattern[]
): StakeholderOutcome[] {
const outcomes: StakeholderOutcome[] = [];
// High-cohesion groups with strong participation are classified as winners
for (const pattern of patterns) {
if (pattern.cohesion > 0.8 && pattern.participation > 0.7) {
outcomes.push({
actor: pattern.group,
outcome: 'winner',
reason: AI_MARKER,
});
} else if (pattern.cohesion < 0.5) {
outcomes.push({
actor: pattern.group,
outcome: 'loser',
reason: AI_MARKER,
});
}
}
// Adopted motions → the proposing side wins
for (const record of records.slice(0, 3)) {
if (record.result?.toLowerCase().includes('adopt')) {
outcomes.push({
actor: 'Majority coalition',
outcome: 'winner',
reason: AI_MARKER,
});
}
}
return outcomes;
}
/**
* Derive action→consequence chains from voting records and anomalies.
*
* @param records - Voting records
* @param anomalies - Detected anomalies
* @returns Action-consequence pairs
*/
function deriveConsequencesFromVoting(
records: readonly VotingRecord[],
anomalies: readonly VotingAnomaly[]
): ActionConsequence[] {
const consequences: ActionConsequence[] = [];
for (const record of records.slice(0, 3)) {
Iif (record.result === PLACEHOLDER_MARKER) continue;
consequences.push({
action: `Vote on "${record.title}" (result: ${record.result}; ${record.votes.for} for, ${record.votes.against} against, ${record.votes.abstain} abstentions)`,
consequence: AI_MARKER,
severity:
Math.abs(record.votes.for - record.votes.against) >
(record.votes.for + record.votes.against) / 2
? 'high'
: 'medium',
});
}
for (const anomaly of anomalies.slice(0, 2)) {
Iif (/placeholder/i.test(anomaly.type)) continue;
const anomalyDescription: string = anomaly.description?.trim() ?? '';
consequences.push({
action:
anomalyDescription.length > 0
? `${anomaly.type} detected: ${anomalyDescription}`
: `${anomaly.type} detected`,
consequence: AI_MARKER,
severity: anomaly.severity?.toLowerCase() === 'high' ? 'high' : 'medium',
});
}
return consequences;
}
/**
* Derive political mistakes from anomalies — defections signal miscalculations.
*
* @param anomalies - Detected voting anomalies
* @returns Political mistake assessments
*/
function deriveMistakesFromAnomalies(anomalies: readonly VotingAnomaly[]): PoliticalMistake[] {
return anomalies
.filter((a) => a.type?.toLowerCase().includes('defect') || a.severity?.toUpperCase() === 'HIGH')
.slice(0, 3)
.map((a) => ({
actor: 'Political group leadership',
description: `${a.type}: ${a.description}`,
alternative: AI_MARKER,
}));
}
/**
* Build multi-stakeholder perspectives for a voting analysis.
* Derives per-group importance scores based on adopted/rejected counts and
* cohesion anomalies.
*
* @param adoptedCount - Number of adopted texts
* @param anomalies - Detected voting anomalies
* @param topic - Primary topic string for context
* @returns Array of stakeholder perspectives
*/
function buildVotingStakeholderPerspectives(
adoptedCount: number,
anomalies: readonly VotingAnomaly[],
topic: string
): StakeholderPerspective[] {
const hasHighAnomalies = anomalies.some((a) => a.severity?.toUpperCase() === 'HIGH');
return buildDefaultStakeholderPerspectives(topic, {
political_groups: hasHighAnomalies ? 0.9 : adoptedCount > 0 ? 0.8 : 0.5,
civil_society: adoptedCount > 0 ? 0.6 : 0.4,
industry: adoptedCount > 0 ? 0.7 : 0.4,
national_govts: 0.7,
citizens: adoptedCount > 0 ? 0.6 : 0.3,
eu_institutions: 0.8,
});
}
/**
* Build the "what" summary for a voting analysis, including intensity metrics.
*
* @param dateFrom - Period start
* @param dateTo - Period end
* @param recordCount - Real voting record count
* @param adoptedCount - Adopted count
* @param rejectedCount - Rejected count
* @param anomalyCount - Anomaly count
* @param patternCount - Pattern count
* @param questionCount - Question count
* @param intensity - Voting intensity metrics (may be null)
* @param polarization - Polarization index (may be null)
* @returns Summary text
*/
function buildVotingWhatText(
dateFrom: string,
dateTo: string,
recordCount: number,
adoptedCount: number,
rejectedCount: number,
anomalyCount: number,
patternCount: number,
questionCount: number,
intensity: VotingIntensity | null,
polarization: PolarizationIndex | null
): string {
if (recordCount === 0 && patternCount === 0 && questionCount === 0) {
return `Parliamentary activity from ${dateFrom} to ${dateTo}. Detailed roll-call data unavailable for this period.`;
}
const base = `${recordCount} votes recorded between ${dateFrom} and ${dateTo}: ${adoptedCount} adopted, ${rejectedCount} rejected. ${anomalyCount} voting anomalies detected across ${patternCount} political groups. ${questionCount} parliamentary questions filed.`;
if (!intensity || recordCount === 0) return base;
return `${base} Voting intensity: ${intensity.closeVoteCount} close ${intensity.closeVoteCount === 1 ? 'vote' : 'votes'}, ${intensity.decisiveVoteCount} decisive ${intensity.decisiveVoteCount === 1 ? 'vote' : 'votes'}. Polarization index: ${polarization?.assessment ?? 'N/A'}.`;
}
/**
* Build the "why" text for a voting analysis.
* Returns AI_MARKER so the AI agent provides real political analysis.
*
* @returns AI_MARKER placeholder for AI-driven analysis
*/
function buildVotingWhyText(): string {
return AI_MARKER;
}
/**
* Build outlook text for voting analysis.
* Returns AI_MARKER — the AI agent provides real forward-looking analysis.
*
* @returns AI_MARKER placeholder
*/
function buildVotingOutlook(): string {
return AI_MARKER;
}
/**
* Build the coalition alignment panel for a voting dashboard.
*
* @param d - Localized dashboard strings
* @param coalition - Coalition metrics
* @returns Panel object or null
*/
function buildVotingCoalitionPanel(
d: DashboardBuilderStrings,
coalition: CoalitionMetrics | null
): DashboardPanel | null {
if (!coalition) return null;
const shiftLabel =
coalition.shiftIndicator === 'strengthening'
? d.coalitionStrengthening
: coalition.shiftIndicator === 'weakening'
? d.coalitionWeakening
: d.coalitionStable;
const shiftTrend: 'up' | 'down' | 'stable' =
coalition.shiftIndicator === 'strengthening'
? 'up'
: coalition.shiftIndicator === 'weakening'
? 'down'
: 'stable';
return {
title: d.coalitionAlignment,
metrics: [
{ label: d.alignmentScore, value: `${coalition.alignmentScore}%`, trend: shiftTrend },
{ label: d.coalitionShift, value: shiftLabel },
],
chart: {
type: 'radar' as const,
title: d.coalitionRadarChart,
data: {
labels: coalition.votingBlocs.map((b) => b.group),
datasets: [
{
label: d.alignmentScore,
data: coalition.votingBlocs.map((b) => b.alignmentScore),
backgroundColor: EP_BLUE_TRANSPARENT,
borderColor: EP_BLUE_BORDER,
},
],
},
},
};
}
/**
* Build the trend panel for a voting dashboard.
*
* @param d - Localized dashboard strings
* @param realRecords - Filtered real voting records
* @param adoptedCount - Number of adopted votes
* @param rejectedCount - Number of rejected votes
* @returns Panel object or null
*/
function buildVotingTrendPanel(
d: DashboardBuilderStrings,
realRecords: readonly VotingRecord[],
adoptedCount: number,
rejectedCount: number
): DashboardPanel | null {
if (realRecords.length < 2) return null;
return {
title: d.trendAnalysis,
metrics: [
{
label: d.adopted,
value: String(adoptedCount),
trend: (adoptedCount > rejectedCount ? 'up' : 'stable') as 'up' | 'down' | 'stable',
},
],
chart: {
type: 'line' as const,
title: d.activityTrendChart,
data: {
labels: realRecords.slice(0, 6).map((r) => r.date ?? ''),
datasets: [
{
label: d.adopted,
data: realRecords
.slice(0, 6)
.map((r) => (r.result?.toLowerCase().includes('adopt') ? 1 : 0)),
borderColor: '#28a745',
backgroundColor: 'rgba(40,167,69,0.1)',
},
],
},
},
};
}
/**
* Build the stakeholder panel for a voting dashboard.
*
* @param d - Localized dashboard strings
* @param patterns - Voting patterns
* @param anomalyCount - Number of voting anomalies
* @returns Panel object or null
*/
function buildVotingStakeholderPanel(
d: DashboardBuilderStrings,
patterns: readonly VotingPattern[],
anomalyCount: number
): DashboardPanel | null {
const stakeholderMetrics = buildStakeholderMetricsFromVoting(patterns, anomalyCount);
return buildStakeholderPanel(d, stakeholderMetrics);
}
/**
* Build stakeholder views for voting multi-dimensional SWOT.
*
* @param adoptedCount - Number of adopted votes
* @param realAnomalies - Non-placeholder anomalies
* @param highSeverity - High-severity anomalies
* @param highCohesion - High-cohesion patterns
* @param lowCohesion - Low-cohesion patterns
* @param realPatterns - Non-placeholder patterns
* @param s - Localized SWOT builder strings
* @returns Stakeholder views map
*/
function buildVotingMDStakeholders(
adoptedCount: number,
realAnomalies: readonly VotingAnomaly[],
highSeverity: readonly VotingAnomaly[],
highCohesion: readonly VotingPattern[],
lowCohesion: readonly VotingPattern[],
realPatterns: readonly VotingPattern[],
s: SwotBuilderStrings
): Partial<Record<StakeholderType, SwotAnalysis>> {
return {
citizen: {
strengths:
adoptedCount > 0
? [{ text: s.votingAdopted(adoptedCount), severity: 'medium' as const }]
: [],
weaknesses:
realAnomalies.length > 0
? [{ text: s.votingAnomalies(realAnomalies.length), severity: 'medium' as const }]
: [],
opportunities: [{ text: s.votingCrossParty, severity: 'medium' as const }],
threats:
highSeverity.length > 0
? [{ text: s.votingHighSeverity(highSeverity.length), severity: 'high' as const }]
: [],
},
mep: {
strengths:
highCohesion.length > 0
? [{ text: s.votingHighCohesion(highCohesion.length), severity: 'high' as const }]
: [],
weaknesses:
lowCohesion.length > 0
? [{ text: s.votingLowCohesion(lowCohesion.length), severity: 'high' as const }]
: [],
opportunities:
realPatterns.length > 0
? [{ text: s.votingDiverseGroups(realPatterns.length), severity: 'medium' as const }]
: [],
threats: [{ text: s.votingShiftingAlliances, severity: 'medium' as const }],
},
};
}
/**
* Build deep analysis for voting-based articles (motions, weekly/monthly review).
*
* @param dateFrom - Period start date
* @param dateTo - Period end date
* @param records - Voting records
* @param patterns - Voting patterns
* @param anomalies - Anomalies detected
* @param questions - Parliamentary questions
* @returns Deep analysis object
*/
export function buildVotingAnalysis(
dateFrom: string,
dateTo: string,
records: readonly VotingRecord[],
patterns: readonly VotingPattern[],
anomalies: readonly VotingAnomaly[],
questions: readonly MotionsQuestion[]
): DeepAnalysis {
const realRecords = records.filter((r) => r.result !== PLACEHOLDER_MARKER);
const realPatterns = patterns.filter((p) => !/placeholder/i.test(p.group));
const realAnomalies = anomalies.filter((a) => !/placeholder/i.test(a.type));
const realQuestions = questions.filter((q) => q.status !== PLACEHOLDER_MARKER);
const adoptedCount = realRecords.filter((r) => r.result?.toLowerCase().includes('adopt')).length;
const rejectedCount = realRecords.filter((r) =>
r.result?.toLowerCase().includes('reject')
).length;
const topTopics = realRecords.slice(0, 3).map((r) => r.title);
// ── Advanced political intelligence ────────────────────────────────────────
const intensity = computeVotingIntensity(realRecords);
const polarization = computePolarizationIndex(realPatterns);
return {
what: buildVotingWhatText(
dateFrom,
dateTo,
realRecords.length,
adoptedCount,
rejectedCount,
realAnomalies.length,
realPatterns.length,
realQuestions.length,
intensity,
polarization
),
who: [
...realPatterns.map(
(p) =>
`${p.group} — cohesion: ${(p.cohesion * 100).toFixed(0)}%, participation: ${(p.participation * 100).toFixed(0)}%`
),
...realQuestions.slice(0, 3).map((q) => `${q.author} — question on "${q.topic}"`),
],
when: [
`Period: ${dateFrom} to ${dateTo}`,
...realRecords.slice(0, 3).map((r) => `${r.date}: Vote on "${r.title}" — ${r.result}`),
],
why: buildVotingWhyText(),
stakeholderOutcomes: deriveStakeholderOutcomesFromVoting(realRecords, realPatterns),
impactAssessment: buildAiMarkerImpactAssessment(),
actionConsequences: deriveConsequencesFromVoting(realRecords, realAnomalies),
mistakes: deriveMistakesFromAnomalies(realAnomalies),
outlook: buildVotingOutlook(),
stakeholderPerspectives: buildVotingStakeholderPerspectives(
adoptedCount,
realAnomalies,
topTopics[0] ?? `voting period ${dateFrom}–${dateTo}`
),
stakeholderOutcomeMatrix: buildOutcomeMatrix([
{
action: `Voting outcomes ${dateFrom}–${dateTo}`,
scores: {
political_groups: realAnomalies.length > 0 ? 0.8 : 0.6,
civil_society: adoptedCount > 0 ? 0.6 : 0.4,
industry: adoptedCount > 0 ? 0.7 : 0.4,
national_govts: 0.7,
citizens: adoptedCount > 0 ? 0.6 : 0.3,
eu_institutions: 0.8,
},
confidence: realRecords.length > 0 ? 'high' : 'low',
},
]),
};
}
/**
* Build SWOT analysis for voting-based articles (motions, weekly/monthly review).
*
* @param records - Voting records
* @param patterns - Voting patterns
* @param anomalies - Detected anomalies
* @param lang - Target language code
* @returns SWOT analysis data
*/
export function buildVotingSwot(
records: readonly VotingRecord[],
patterns: readonly VotingPattern[],
anomalies: readonly VotingAnomaly[],
lang: LanguageCode = 'en'
): SwotAnalysis {
const s: SwotBuilderStrings = getLocalizedString(SWOT_BUILDER_STRINGS, lang);
const realRecords = records.filter((r) => r.result !== PLACEHOLDER_MARKER);
const realPatterns = patterns.filter((p) => !/placeholder/i.test(p.group));
const realAnomalies = anomalies.filter((a) => !/placeholder/i.test(a.type));
const adoptedCount = realRecords.filter((r) => r.result?.toLowerCase().includes('adopt')).length;
const highCohesionGroups = realPatterns.filter((p) => p.cohesion > 0.8);
const lowCohesionGroups = realPatterns.filter((p) => p.cohesion < 0.5);
const highSeverityAnomalies = realAnomalies.filter((a) => a.severity?.toUpperCase() === 'HIGH');
return {
strengths: [
...(highCohesionGroups.length > 0
? [
{
text: s.votingHighCohesion(highCohesionGroups.length),
severity: 'high' as const,
},
]
: []),
...(adoptedCount > 0
? [
{
text: s.votingAdopted(adoptedCount),
severity: 'medium' as const,
},
]
: []),
...(realRecords.length > 0
? [
{
text: s.votingActiveVotes(realRecords.length),
severity: 'medium' as const,
},
]
: []),
],
weaknesses: [
...(lowCohesionGroups.length > 0
? [
{
text: s.votingLowCohesion(lowCohesionGroups.length),
severity: 'high' as const,
},
]
: []),
...(realAnomalies.length > 0
? [
{
text: s.votingAnomalies(realAnomalies.length),
severity: 'medium' as const,
},
]
: []),
],
opportunities: [
{
text: s.votingCrossParty,
severity: 'medium' as const,
},
...(realPatterns.length > 0
? [
{
text: s.votingDiverseGroups(realPatterns.length),
severity: 'medium' as const,
},
]
: []),
],
threats: [
...(highSeverityAnomalies.length > 0
? [
{
text: s.votingHighSeverity(highSeverityAnomalies.length),
severity: 'high' as const,
},
]
: []),
{
text: s.votingShiftingAlliances,
severity: 'medium' as const,
},
],
};
}
/**
* Build dashboard for voting-based articles (motions, weekly/monthly review).
* Includes a coalition alignment radar chart and stakeholder impact scorecard.
*
* @param records - Voting records
* @param patterns - Voting patterns
* @param anomalies - Detected anomalies
* @param lang - Target language code
* @returns Dashboard configuration with coalition and stakeholder intelligence
*/
export function buildVotingDashboard(
records: readonly VotingRecord[],
patterns: readonly VotingPattern[],
anomalies: readonly VotingAnomaly[],
lang: LanguageCode = 'en'
): DashboardConfig {
const d: DashboardBuilderStrings = getLocalizedString(DASHBOARD_BUILDER_STRINGS, lang);
const realRecords = records.filter((r) => r.result !== PLACEHOLDER_MARKER);
const realPatterns = patterns.filter((p) => !/placeholder/i.test(p.group));
const realAnomalies = anomalies.filter((a) => !/placeholder/i.test(a.type));
const adoptedCount = realRecords.filter((r) => r.result?.toLowerCase().includes('adopt')).length;
const rejectedCount = realRecords.filter((r) =>
r.result?.toLowerCase().includes('reject')
).length;
const overviewPanel = {
title: d.votingOverview,
metrics: [
{ label: d.totalVotes, value: String(realRecords.length), trend: 'stable' as const },
{
label: d.adopted,
value: String(adoptedCount),
trend: adoptedCount > 0 ? ('up' as const) : ('stable' as const),
},
{ label: d.rejected, value: String(rejectedCount) },
{ label: d.anomalies, value: String(realAnomalies.length) },
],
};
const cohesionPanel =
realPatterns.length > 0
? {
title: d.politicalGroupCohesion,
metrics: realPatterns.slice(0, 4).map((p) => ({
label: p.group,
value: `${(p.cohesion * 100).toFixed(0)}%`,
trend: (p.cohesion > 0.8 ? 'up' : p.cohesion < 0.5 ? 'down' : 'stable') as
| 'up'
| 'down'
| 'stable',
})),
chart: {
type: 'bar' as const,
title: d.groupCohesionRates,
data: {
labels: realPatterns.slice(0, 6).map((p) => p.group),
datasets: [
{
label: d.cohesionPct,
data: realPatterns.slice(0, 6).map((p) => Math.round(p.cohesion * 100)),
},
],
},
},
}
: null;
const coalition = buildCoalitionMetricsFromPatterns(realPatterns);
const coalitionPanel = buildVotingCoalitionPanel(d, coalition);
const trendPanel = buildVotingTrendPanel(d, realRecords, adoptedCount, rejectedCount);
const stakeholderPanel = buildVotingStakeholderPanel(d, realPatterns, realAnomalies.length);
const panels = [
overviewPanel,
...(cohesionPanel ? [cohesionPanel] : []),
...(coalitionPanel ? [coalitionPanel] : []),
...(trendPanel ? [trendPanel] : []),
...(stakeholderPanel ? [stakeholderPanel] : []),
];
return { panels };
}
/**
* Build intelligence mindmap for voting analysis articles.
*
* Constructs a policy domain intelligence map with political group nodes
* as the primary domain layer, voting pattern sub-topics, and anomaly actors.
*
* @param records - Voting records for the period
* @param patterns - Political group voting pattern data
* @param anomalies - Detected voting anomalies
* @param _lang - Reserved for future localisation (default: 'en')
* @returns Intelligence mindmap data, or null when all data is placeholder
*/
export function buildVotingMindmap(
records: readonly VotingRecord[],
patterns: readonly VotingPattern[],
anomalies: readonly VotingAnomaly[],
_lang: LanguageCode = 'en'
): IntelligenceMindmap | null {
void _lang;
const realRecords = records.filter((r) => r.result !== PLACEHOLDER_MARKER);
const realPatterns = patterns.filter((p) => !/placeholder/i.test(p.group));
const realAnomalies = anomalies.filter((a) => !/placeholder/i.test(a.type));
if (realPatterns.length === 0) return null;
const domainNodes: MindmapNode[] = realPatterns.slice(0, 8).map((p, i) => {
const cohesion = p.cohesion ?? 0;
const children: MindmapNode[] = realRecords
.filter((r) => r.result !== PLACEHOLDER_MARKER)
.slice(0, 3)
.map((r, ri) => ({
id: `record-${i}-${ri}`,
label: r.title.slice(0, 50),
category: 'action' as const,
influence: r.votes.for / Math.max(1, r.votes.for + r.votes.against + r.votes.abstain),
color: r.result?.toLowerCase().includes('adopt') ? 'green' : 'red',
children: [],
metadata: { documentRef: r.title.slice(0, 30) },
}));
return {
id: `group-${i}`,
label: p.group,
category: 'policy_domain' as const,
influence: cohesion,
color: cohesion > 0.8 ? 'green' : cohesion > 0.5 ? 'cyan' : 'red',
children,
metadata: { politicalGroup: p.group },
};
});
const actorNetwork: ActorNode[] = [
...realPatterns.slice(0, 6).map((p, i) => ({
id: `actor-group-${i}`,
name: p.group,
type: 'group' as const,
influence: p.cohesion ?? 0,
connections: realAnomalies
.filter((a) => a.type && !a.type.includes('placeholder'))
.slice(0, 2)
.map((_, ai) => `anomaly-${ai}`),
})),
...realAnomalies.slice(0, 3).map((a, i) => ({
id: `anomaly-${i}`,
name: a.type,
type: 'external' as const,
influence: a.severity?.toUpperCase() === 'HIGH' ? 0.9 : 0.5,
connections: [],
})),
];
const anomalyActorCount = Math.min(realAnomalies.length, 3);
const connections: PolicyConnection[] = realAnomalies.slice(0, anomalyActorCount).map((a, i) => ({
from: `anomaly-${i}`,
to: `group-${i % Math.max(1, domainNodes.length)}`,
strength: a.severity?.toUpperCase() === 'HIGH' ? 'strong' : 'moderate',
type: 'political' as const,
evidence: a.type,
}));
const adoptedCount = realRecords.filter((r) => r.result?.toLowerCase().includes('adopt')).length;
return {
centralTopic: 'Voting Intelligence Analysis',
layers: [{ depth: 1, nodes: domainNodes }],
connections,
actorNetwork,
stakeholderGroups: ['Political Groups', CIVIL_SOCIETY, 'Member States'],
summary: `Analysing ${realRecords.length} votes across ${realPatterns.length} political groups. ${adoptedCount} measures adopted.`,
};
}
/**
* Build multi-dimensional SWOT analysis for voting-based articles.
*
* Produces dimension-specific breakdowns (political, economic, social,
* legal, geopolitical), temporal assessments, and stakeholder views
* derived from voting records, patterns, and anomaly data.
*
* @param records - Voting records
* @param patterns - Voting patterns
* @param anomalies - Detected anomalies
* @param lang - Target language code
* @returns Multi-dimensional SWOT data
*/
export function buildVotingMultiDimensionalSwot(
records: readonly VotingRecord[],
patterns: readonly VotingPattern[],
anomalies: readonly VotingAnomaly[],
lang: LanguageCode = 'en'
): MultiDimensionalSwot {
const s: SwotBuilderStrings = getLocalizedString(SWOT_BUILDER_STRINGS, lang);
const base = buildVotingSwot(records, patterns, anomalies, lang);
const realRecords = records.filter((r) => r.result !== PLACEHOLDER_MARKER);
const realPatterns = patterns.filter((p) => !/placeholder/i.test(p.group));
const realAnomalies = anomalies.filter((a) => !/placeholder/i.test(a.type));
const adoptedCount = realRecords.filter((r) => r.result?.toLowerCase().includes('adopt')).length;
const highCohesion = realPatterns.filter((p) => p.cohesion > 0.8);
const lowCohesion = realPatterns.filter((p) => p.cohesion < 0.5);
const highSeverity = realAnomalies.filter((a) => a.severity?.toUpperCase() === 'HIGH');
const political = makeDimension(
'political',
highCohesion.length > 0
? [{ text: s.votingHighCohesion(highCohesion.length), severity: 'high' as const }]
: [],
lowCohesion.length > 0
? [{ text: s.votingLowCohesion(lowCohesion.length), severity: 'high' as const }]
: [],
[{ text: s.votingCrossParty, severity: 'medium' as const }],
highSeverity.length > 0
? [{ text: s.votingHighSeverity(highSeverity.length), severity: 'high' as const }]
: []
);
const economic = makeDimension(
'economic',
adoptedCount > 0 ? [{ text: s.votingAdopted(adoptedCount), severity: 'medium' as const }] : [],
[],
realPatterns.length > 0
? [{ text: s.votingDiverseGroups(realPatterns.length), severity: 'medium' as const }]
: [],
[{ text: s.votingShiftingAlliances, severity: 'medium' as const }]
);
const social = makeDimension(
'social',
realRecords.length > 0
? [{ text: s.votingActiveVotes(realRecords.length), severity: 'medium' as const }]
: [],
realAnomalies.length > 0
? [{ text: s.votingAnomalies(realAnomalies.length), severity: 'medium' as const }]
: [],
[],
[]
);
const legal = makeDimension(
'legal',
adoptedCount > 0 ? [{ text: s.votingAdopted(adoptedCount), severity: 'medium' as const }] : [],
[],
[],
highSeverity.length > 0
? [{ text: s.votingHighSeverity(highSeverity.length), severity: 'high' as const }]
: []
);
const geopolitical = makeDimension(
'geopolitical',
[],
lowCohesion.length > 0
? [{ text: s.votingLowCohesion(lowCohesion.length), severity: 'medium' as const }]
: [],
highCohesion.length > 0
? [{ text: s.votingHighCohesion(highCohesion.length), severity: 'medium' as const }]
: [],
[{ text: s.votingShiftingAlliances, severity: 'medium' as const }]
);
const temporal: TemporalSwotAssessment = {
shortTerm: base,
mediumTerm: {
strengths: base.strengths.filter((i) => i.severity === 'high'),
weaknesses: base.weaknesses.filter((i) => i.severity === 'high'),
opportunities: base.opportunities,
threats: base.threats.filter((i) => i.severity === 'high'),
},
};
const stakeholderViews = buildVotingMDStakeholders(
adoptedCount,
realAnomalies,
highSeverity,
highCohesion,
lowCohesion,
realPatterns,
s
);
return {
title: base.title,
dimensions: [political, economic, social, legal, geopolitical],
temporal,
stakeholderViews,
};
}
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