Module: IndividualIntelligence/PoliticianProfiling

Individual Politician Career Analytics & Risk Intelligence Dashboard

Advanced intelligence profiling platform providing micro-level politician assessment across 349 Swedish members of parliament. Implements comprehensive risk scoring, influence hierarchy measurement, behavioral pattern analysis, and career trajectory forecasting using Chart.js and D3.js visualization. Monitors individual politician performance, behavioral anomalies, and career risk factors.

Intelligence Methodology

This module implements individual-level political intelligence profiling:

  • Target Population: 349 Swedish parliamentarians (Riksdagen members)
  • Analysis Dimensions: Risk, influence, behavioral patterns, career trajectory
  • Temporal Coverage: Full parliamentary career from first election to present
  • Granularity: Individual-level assessment with peer comparison context

Individual Politician Intelligence Framework

Five-Dimensional Analysis Taxonomy:

  1. Risk Assessment (Individual Threat Profile)

    • Ethics violations and conduct concerns
    • Electoral vulnerability and reelection risk
    • Political isolation and coalition weakness
    • Career stability and burnout indicators
    • Personal scandal and reputation exposure
  2. Influence Measurement (Individual Power Assessment)

    • Committee assignments and leadership roles
    • Speaking frequency and discourse leadership
    • Coalition-building capability and ally networks
    • Media prominence and public visibility
    • Decision-making authority in party structures
  3. Behavioral Pattern Analysis (Anomaly Detection)

    • Voting deviation from party discipline
    • Attendance and participation consistency
    • Speech content and rhetoric evolution
    • Committee engagement and activity levels
    • Coalition alliance volatility and shifts
  4. Career Trajectory (Professional Development)

    • Years of service and experience levels
    • Role progression (backbencher → committee → leadership)
    • Electoral performance trends
    • Party assignments and responsibilities
    • Generational cohort and peer advancement
  5. Influence Bucket Classification (Politician Tiers)

    • Leadership tier (party leaders, cabinet ministers)
    • Influential tier (committee chairs, opinion leaders)
    • Standard tier (regular parliamentarians)
    • New/junior tier (first-term or new assignments)

Data Sources (CIA Platform)

Primary Intelligence Feeds:

  • view_politician_risk_summary_sample.csv

    • Fields: politician_id, name, party, risk_score (0-10), risk_level, risk_categories
    • Scope: Risk assessment for 349 individual MPs
    • Use: Risk profiling, threat identification, risk-based sorting
  • view_riksdagen_politician_influence_metrics_sample.csv

    • Fields: politician_id, name, influence_score (0-100), leadership_roles, speech_frequency
    • Scope: Individual influence measurement with component breakdown
    • Use: Influence hierarchy visualization, power assessment
  • view_politician_behavioral_trends_sample.csv

    • Fields: politician_id, year, voting_deviation_pct, attendance_rate, speech_sentiment
    • Scope: Annual behavioral metrics for anomaly detection
    • Use: Behavioral pattern recognition, consistency assessment
  • distribution_experience_levels.csv

    • Fields: politician_id, years_service, parliament_term_count, experience_level, avg_roles
    • Scope: Career experience and tenure statistics
    • Use: Experience profiling, junior/senior categorization
  • distribution_influence_buckets.csv

    • Fields: politician_id, influence_bucket (leadership/influential/standard/junior), bucket_rank
    • Scope: Categorization of 349 MPs into influence tiers
    • Use: Tier-based analysis, leadership pipeline tracking
  • distribution_assignment_roles.csv

    • Fields: politician_id, role_type, role_count, committee_assignments, leadership_count
    • Scope: Individual role assignments and responsibilities
    • Use: Role trajectory tracking, responsibility assessment

OSINT Collection Strategy

Multi-Layer Individual Intelligence:

  1. Parliamentary Records: Voting records, speeches, committee participation
  2. Media Monitoring: Coverage volume, sentiment, scandal tracking
  3. Social Media: Engagement metrics, online presence, supporter networks
  4. Personal Background: Declared conflicts, financial interests, organizational affiliations
  5. Electoral History: Campaign performance, vote trends, constituency dynamics
  6. Network Analysis: Coalition patterns, ally/rival relationships, influence circles
  7. Behavioral Metrics: Speech analysis, consistency assessment, sentiment tracking

Visualization Intelligence

Chart.js Risk Summary (Primary):

  • Risk Distribution Chart: Population-wide risk distribution
    • Histogram showing risk score distribution across 349 MPs
    • Color-coded risk levels (green/yellow/orange/red)
    • Shows critical/high-risk outliers

Chart.js Influence Metrics (Power Assessment):

  • Influence Ranking Chart: Top 50 most influential politicians
    • Horizontal bar chart ranked by influence score
    • Color segments for influence dimensions
    • Identifies power concentration vs. distributed influence

Chart.js Behavioral Trends (Anomaly Detection):

  • Behavioral Pattern Timeline: Individual politician behavior over time
    • Multi-line chart showing voting deviation and participation trends
    • Identifies consistency, volatility, or anomalies
    • Flags behavioral changes and pattern breaks

Chart.js Experience Distribution (Career):

  • Experience Levels: Distribution across experience categories
    • Grouped bar chart showing tenure statistics
    • Identifies junior/senior ratios and generational balance
    • Shows parliamentary turnover rates

Chart.js Role Distribution (Responsibility):

  • Assignment Roles: Distribution of parliamentary roles
    • Stacked bar showing committee, leadership, and regular roles
    • Highlights responsibility concentration
    • Shows role progression paths

Intelligence Analysis Frameworks Applied

Version:
  • 1.0.0
Since:
  • 2024
Author:
  • Hack23 AB - Individual Intelligence Team
License:
  • Apache-2.0
Source:
See:

Methods

(inner) createCareerTrajectoryChart(data)

Create career trajectory line chart from behavioral trends data Shows attendance, effectiveness, and discipline trends over time

Parameters:
Name Type Description
data Array

Behavioral trends data from CIA CSV

Source:

(inner) createExperienceDistributionChart(data)

Create experience distribution bar chart from real CIA data

Parameters:
Name Type Description
data Array

Experience distribution data from distribution_experience_levels.csv

Source:

(inner) createProductivityInfluenceChart(riskData, influenceData)

Create productivity vs influence scatter chart from real CIA data Uses risk_summary (productivity proxy via documents/votes) and influence_metrics

Parameters:
Name Type Description
riskData Array

Risk summary data with vote counts and documents

influenceData Array

Influence metrics with network connections

Source:

(async, inner) fetchCIAData(urls) → {Promise.<Array>}

Fetch CSV data with local-first, remote-fallback strategy

Parameters:
Name Type Description
urls Array.<string>

Array of [localUrl, remoteUrl]

Source:
Returns:

Parsed CSV data

Type
Promise.<Array>

(async, inner) loadDashboardData()

Load all dashboard data from real CIA CSV files Uses local-first with remote-fallback for each data source

Source:

(inner) parseCSV(csvText) → {Array.<Object>}

Parse CSV text to array of objects

Parameters:
Name Type Description
csvText string

CSV text content

Source:
Returns:

Parsed data

Type
Array.<Object>

(inner) parseCSVLine(line) → {Array.<string>}

Parse a single CSV line handling quoted fields

Parameters:
Name Type Description
line string

CSV line

Source:
Returns:

Parsed values

Type
Array.<string>

(inner) renderTop10List(containerId, data, scoreLabel)

Render Top 10 list

Parameters:
Name Type Default Description
containerId string

Container element ID

data Array

Top 10 data

scoreLabel string Score

Label for score column

Source:

(inner) showError(message)

Show error message

Parameters:
Name Type Description
message string

Error message

Source: