Our Methodology

Coreification uses a systematic, multi-source approach to discover, analyze, and document fashion subcultures. Here's how we build the world's most comprehensive fashion intelligence platform.

Discovery Process

Our discovery agents continuously monitor multiple sources to identify emerging and established cores:

  • Social platforms (TikTok, Instagram, Pinterest, Reddit)
  • Fashion media and publications
  • Runway shows and designer collections
  • Street style photography
  • Fashion forums and communities
  • Music and cultural movements

Documentation Framework

Each core undergoes comprehensive analysis across multiple dimensions:

Core Attributes

  • Identity: Name, alternative names, slug
  • Description: Concise definition and characteristics
  • Origin: Historical emergence and cultural context
  • Era: Time period and evolution
  • Status: Emerging, established, fading, or revival
  • Key Garments: Defining clothing items
  • Silhouettes: Characteristic shapes and fits
  • Materials: Favored fabrics and textures
  • Color Palettes: Primary, secondary, and accent colors
  • Brands: Core, adjacent, and inspired brands
  • Music: Associated genres and artists
  • Regions: Geographic popularity

Relationship Mapping

We map five types of relationships between cores:

  • Influenced By: Parent cores that shaped this aesthetic
  • Influences: Cores that emerged from or were inspired by this one
  • Sub-Cores: Direct variations and specializations
  • Related Cores: Adjacent or overlapping aesthetics
  • Opposition To: Cores defined in contrast to this one

Trend Scoring

Our trend score (0-100) reflects current cultural momentum based on:

  • Search volume trends
  • Social media mentions and hashtag usage
  • Media coverage frequency
  • Brand adoption and runway appearances
  • Community growth and engagement

AI-Assisted Research

We leverage advanced AI models to accelerate research while maintaining quality:

  • Pattern recognition across vast fashion data sources
  • Automated initial documentation and structuring
  • Relationship inference based on aesthetic similarities
  • Continuous monitoring for updates and changes
  • Natural language analysis of fashion discourse

Quality Standards

Every core entry must meet our quality criteria:

  • Cultural Significance: Evidence of community adoption
  • Aesthetic Coherence: Clear visual and stylistic identity
  • Historical Context: Documented origin and evolution
  • Distinguishability: Meaningfully distinct from existing cores
  • Source Verification: Multiple independent sources

Continuous Updates

Fashion is dynamic. We continuously update cores with:

  • New brand associations and collaborations
  • Evolution in key garments and aesthetics
  • Emerging sub-cores and variations
  • Status changes (emerging → established, etc.)
  • Cultural context updates

Transparency & Accuracy

We're committed to building the most accurate and comprehensive fashion knowledge base. Each core displays its last update date, and we welcome feedback from the community to refine our documentation. Our goal is not perfection on day one, but continuous improvement toward definitive fashion intelligence.