Influence Atlas

Context for expert authenticity

An interactive index of 324 influential figures evaluated through a Behavioral Humanism framework.

This application provides rich, searchable profiles of 324+ influential figures across various domains including technology, business, psychology, philosophy, design, film, legal, culinary arts, journalism, medical specialties, and more. Each profile includes detailed behavioral traits, communication patterns, decision-making styles, and psychological characteristics.

• Rich Profile Data: 320+ standardized traits across 23 behavioral categories
• Advanced Filtering: 28+ filters including 10 Behavioral Humanism dimensions + 6 Tier 1/2 categories
• Quality Tier Filtering: Filter by Legend, Pioneer, or Contemporary profiles
• Trait-Based Discovery: Click any trait chip to find similar profiles
• Hierarchical Color System: Color-coded traits by category with automatic contrast adjustment for accessibility
• Full-Screen Detail View: Clean category cards with clickable trait chips
• Responsive Design: Works seamlessly across desktop and mobile devices
• Cross-Browser Compatible: Tested on Chrome, Firefox, and Safari
• Comprehensive Export Functions: Export profiles in JSON (complete data), Markdown (formatted), or YAML (AI persona injection ready) with full behavioral humanism dimensions
• Performance Optimized: 23.6% smaller file size with index-based filtering

• 324 Profiles: Industry leaders, innovators, and influential thinkers
• 37 Role-Based Archetypes: Systematic, role-based taxonomy (Visionary, Designer, Scholar, etc.)
• 29 Domains: Primary fields of work (Technology, Marketing, Philosophy, Music, etc.)
• 164 Subdomains: Specialized areas within domains
• 23 Behavioral Categories: Comprehensive framework including Behavioral Humanism + Tier 1/2
• 320+ Standardized Traits: Consolidated and verified characteristics
• 170 Data Fields: Comprehensive profile attributes with 90%+ coverage
• Quality Tiers: Legend (68), Pioneer (232), Contemporary (18)

Profiles are evaluated through an integrated framework combining:

• Daniel Kahneman's Behavioral Economics: Cognitive biases, decision-making patterns, System 1/2 thinking
• Abraham Maslow's Humanistic Psychology: Self-actualization, growth motivation, human needs hierarchy

Behavioral Humanism (7 filterable dimensions):

1. Bias Awareness: Understanding of cognitive biases and mitigation strategies
2. Growth Motivation: Intrinsic drivers and learning orientation
3. Cognitive Humanism: Empathy, ethical frameworks, human-centered thinking
4. Humanistic Cognition: Creative problem solving and holistic perspective
5. Human Needs Hierarchy: Maslow's hierarchy indicators and fulfillment patterns
6. Self Actualization: Peak experiences, autonomy, purpose alignment
7. Behavioral Growth: Adaptation patterns and resilience indicators

Tier 1 Expansion (3 modern dimensions - v9.0): 8. Technology Relationship: Technology adoption, digital fluency, AI perspective 9. Crisis Response: Stress patterns, failure recovery, uncertainty tolerance 10. Influence Style: Persuasion approach, rhetoric style, change mechanism

Tier 2 Expansion (3 interpersonal dimensions - v10.0): 11. Resource Relationship: Wealth perspective, generosity patterns, financial risk appetite 12. Time Orientation: Time horizon, legacy concern, intergenerational thinking 13. Collaboration Enhancement: Conflict resolution, mentorship, delegation approach

Traditional Categories (17 additional):

• Psychological Profile
• Communication Style & Communication
• Collaboration
• Domain Expertise
• Behavioral Patterns
• Learning
• Values
• Cultural Context
• Temporal Context
• Background & Experience
• And more...

• Frontend: Vanilla JavaScript, HTML5, CSS3
• Styling: Custom CSS with hierarchical color system (4 levels per category)
• Data Format: Optimized JSON with index-based filtering
• Performance: 23.6% smaller file size, memoized search, debounced input
• Testing: Playwright for cross-browser compatibility
• Accessibility: WCAG 2.1 AA compliant with automatic contrast adjustment
• Data Quality: Python scripts for gap analysis and trait standardization

Live Demo: https://raymassie.github.io/influence-atlas/

Repository: https://github.com/raymassie/influence-atlas

• 324 profiles with comprehensive, standardized trait data
• 20 new legend profiles added (sports, music, arts, philosophy, fashion, architecture, writing, civil rights)
• Systematic archetype rebuild - 37 role-based archetypes (not field-specific)
• Quality tier filtering - Legend, Pioneer, Contemporary categories
• Performance optimizations - 23.6% smaller file size, index-based filtering
• 7 Behavioral Humanism filters fully integrated
• 90%+ field coverage across all profiles
• 3,887 traits standardized to lowercase convention
• Hierarchical color system with WCAG AA compliance
• Cross-browser tested (Chrome, Firefox, Safari)
• Advanced filtering with 25+ filter dimensions
• Clickable trait chips for instant discovery
• Full documentation with inline comments

• Excellent Coverage (≥90%): 10 fields
• Good Coverage (70-89%): 6 fields
• Medium Coverage (50-69%): 12 fields
• Critical fields reduced by 68% (19 → 6)

• Enhanced search functionality: Type-safe character-based substring matching with improved reliability
• Comprehensive export formats: Markdown and YAML now include full behavioral humanism dimensions (15+ sections)
• Complete archetype system rebuild: Systematic, role-based taxonomy
• Performance optimizations: 23.6% file size reduction, index-based filtering
• Quality tier implementation: Functional Legend/Pioneer/Contemporary filters
• Archetype corrections: 100+ profiles updated with accurate role assignments
• Visionary refinement: Reduced from 11 to 4 true visionaries (1.3% of profiles)
• Field-specific elimination: Converted Psychologist, Economist, etc. to role-based
• Search optimization: Memoized results, debounced input, cached queries
• Index files: Archetype, domain, quality tier, and search indexes for faster filtering

• Profile comparison tools (side-by-side view)
• Advanced trait analytics and visualizations
• Export to additional formats
• Additional service industry domains (politics, sports, etc.)

All profile data follows strict quality guidelines:

• Factually-Grounded: Based on documented, publicly available information
• Verifiable: No speculation or invented characteristics
• Pattern-Based: Intelligent gap filling uses existing profile patterns
• Standardized: All traits follow lowercase convention for consistency
• Comprehensive: 155 data fields per profile with 90%+ average coverage

• Automated coverage analysis across all profiles
• Trait standardization verification scripts
• Cross-browser compatibility testing
• Regular data integrity checks

This project is licensed under the Influence Atlas License - see the LICENSE file for details.

Quick Summary:

• ✅ Permitted: Educational, research, personal, and non-commercial use
• ❌ Prohibited: Commercial use without written permission
• 📧 Commercial Licensing: Contact via GitHub Issues for commercial use permissions

This license protects the dataset from commercial exploitation while keeping it open for legitimate educational and research purposes.

This is a research and reference project. Profile data is continuously being refined and expanded.

For detailed release notes, see RELEASE-NOTES.md.