Guided case study
A three-stage pathway from the site's structural-analysis model through an operational research method to an applied semantic-network case study.
Begin with the general explanation of hidden structure, follow the operational research pipeline, then inspect its application to the Dan John transcript corpus. A Python reference and a parallel TikTok study provide supporting context.
This order records the argument, rather than merely grouping pages that share vocabulary.
Core explainer
The conceptual foundation for locating statistical, relational and semantic structure in large bodies of content.
Methodology
A multi-stage constraint system that reconstructs, filters, and stress-tests a search-space to identify which semantic structures are stable enough to act on.
Interactive case study
What 382 Dan John strength-coaching transcripts reveal about the recurring decisions behind his programmes, with source-linked evidence, interactive network analysis and reproducible code.
These pages provide methodology, summaries, parallel case studies or alternate media for the main sequence.
Methodology
A plain-language companion to the SEO Python codebase, explaining how the workflow uses search-result collection, NLP text processing, keyphrase extraction, embeddings, network analysis, and association rule mining for semantic SEO research.
Parallel case study
How a Python pipeline turns TikTok search results, metadata, captions and transcripts into a reusable ChatGPT handoff for analysing trends and generating new video concepts.