Module: TemporalIntelligence/SeasonalAnalysis

Swedish Parliamentary Seasonal Activity Analysis & Quarterly Pattern Intelligence Dashboard

Advanced intelligence analysis platform implementing 23-year temporal pattern analysis (2002-2025) of Swedish parliamentary quarterly activity with sophisticated Z-score anomaly detection and seasonal pattern classification. Identifies systematic quarterly variations, detects activity anomalies, and classifies seasonal patterns through multi-year aggregation and cross-quarter comparative analysis using D3.js and Chart.js visualization.

Intelligence Methodology

This module implements temporal pattern intelligence analysis:

• Historical Scope: 23 years × 4 quarters = 92 quarterly data points
• Analysis Approach: Seasonal decomposition with Z-score anomaly detection
• Granularity: Quarterly activity aggregation across parliamentary entities
• Anomaly Threshold: Z-score ≥ 2.0 (p<0.05) for statistical significance

Seasonal Intelligence Framework

Four-Dimensional Analysis Taxonomy:

1. Quarterly Activity Patterns (Seasonal Decomposition)

   • Q1 (January-March): Spring session, budget discussions beginning
   • Q2 (April-June): Legislative focus, committee work intensification
   • Q3 (July-September): Summer recess, reduced activity baseline
   • Q4 (October-December): Fall session, pre-election activity surge
   • Activity types: Ballots, documents, committee decisions, attendance

2. Z-Score Anomaly Detection (Statistical Outlier Identification)

   • Baseline: Mean and standard deviation per quarter (23 years)
   • Z-score calculation: (Value - Mean) / StdDev
   • Anomaly threshold: |Z-score| ≥ 2.0 (95% confidence)
   • Classification: Normal, Elevated, Anomaly, Critical

3. Seasonal Pattern Classification (Behavioral Categorization)

   • Normal: Activity within ±1 StdDev of quarterly average
   • Elevated: Activity 1-2 StdDev above/below average
   • Anomaly: Activity >2 StdDev from average (statistical outlier)
   • Critical: Extreme anomaly >3 StdDev (very rare events)

4. Cross-Year Quarter Comparison (Temporal Consistency)

   • Year-over-year quarter consistency analysis
   • Trend identification within same quarter across years
   • Activity volatility assessment by quarter
   • Quarter-to-quarter transition patterns

Data Sources (CIA Platform)

Primary Intelligence Feeds:

• view_riksdagen_seasonal_activity_patterns_sample.csv
  • Fields: year, quarter, ballot_count, document_count, decision_count, attendance_rate, avg_speech_length, committee_meetings, anomaly_score, anomaly_class
  • Scope: 23 years (2002-2025) × 4 quarters = 92 quarterly records
  • Use: Seasonal pattern baseline, anomaly detection, quarterly benchmarking
  • Coverage: Full spectrum of parliamentary activity metrics

OSINT Collection Strategy

Temporal Pattern Intelligence:

1. Parliamentary Activity Tracking: Vote counts, document filings, committee meetings
2. Attendance Intelligence: Member participation rates, session attendance patterns
3. Speech Analytics: Contribution frequency, speech length, rhetoric intensity
4. Calendar Intelligence: Recess periods, session schedules, emergency sessions
5. Budget Cycles: Fiscal year boundaries and budget discussion phases
6. Electoral Calendars: Election-adjacent activity surge patterns
7. Government Transitions: Cabinet change and policy uncertainty impact on activity

Visualization Intelligence

D3.js Quarterly Heat Map (Primary):

• 23×4 Matrix Visualization: Years (Y-axis) × Quarters (X-axis)
  • Each cell represents quarterly activity level
  • Color intensity: Activity magnitude (blue/low → red/high)
  • Color saturation: Anomaly magnitude (white/normal → black/critical)
  • Interactive: Tooltip reveals detailed metrics (count, Z-score, classification)
  • Scrollable: 23 years with year labels and Q1-Q4 grid
  • Sortable: By activity level, anomaly score, or time sequence

Chart.js Seasonal Decomposition (Pattern Analysis):

• Box-and-Whisker Plot by quarter across 23 years:
  • X-axis: 4 quarters (Q1, Q2, Q3, Q4)
  • Y-axis: Activity metric value
  • Box: Interquartile range (25th-75th percentile)
  • Line: Median (50th percentile)
  • Whiskers: 1.5×IQR range
  • Points: Outliers beyond whiskers (statistical anomalies)
  • Shows quarterly pattern consistency and outlier years

Chart.js Anomaly Timeline (Outlier Tracking):

• Anomaly Score Time Series: Z-scores for all quarters
  • Multi-line chart with threshold bands
  • Separate lines for different activity types
  • Horizontal reference lines at Z=0, Z=2, Z=-2, Z=3, Z=-3
  • Color-coded zones: Green (normal), Yellow (elevated), Red (anomaly)
  • Identifies anomalous quarters and their characteristics

Chart.js Quarter Comparison (Relative Strength):

• Average Activity by Quarter: Multi-year aggregated pattern
  • Bar chart showing Q1, Q2, Q3, Q4 average activities
  • Error bars showing ±1 StdDev confidence bands
  • Shows expected seasonal variation
  • Identifies which quarters are typically high/low activity

Chart.js Activity Quartile Distribution (Ranking):

• Quartile Membership Heat Map: Each quarter's historical ranking
  • Shows frequency of each quarter landing in quartiles
  • Q1 column: How often Q1s rank in top/bottom quartiles
  • Helps identify most/least reliable quarters

Intelligence Analysis Frameworks Applied