Augmented Hierarchy of Needs (AHN): YouTube Comment Corpus — Digital Motivation Analysis Across Five AHN Levels (n=1,403 comments, April 2026)

This dataset contains 1,403 YouTube comments collected via the YouTube Data API v3 (April 2026) across five search queries targeting digital disconnection, nomophobia, cortisol/stress responses to digital separation, AI identity threat, and algorithmic manipulation. The corpus serves as the primary empirical validation dataset for the Augmented Hierarchy of Needs (AHN) framework — a post-digital reconstruction of Maslow's (1943) Hierarchy of Needs integrating Self-Determination Theory (Deci & Ryan, 1985), the Extended Mind Thesis (Clark & Chalmers, 1998), and Psychological Contract Theory (Rousseau, 1995). AHN Level Distribution (expanded lexicon v2, n=1,403):- L1 Digital Physiological: 340 comments (24.2%) — highest- L3 Algorithmic Belonging: 130 comments (9.3%)- L5 Post-Human Self-Actualisation: 45 comments (3.2%)- L2 Digital Safety: 43 comments (3.1%)- L4 Cognitive Avatarisation: 30 comments (2.1%)- Uncategorised: 815 comments (58.1%) Mean marker density:- L1: 0.4825 per comment- L3: 0.2281 per comment- L5: 0.0748 per comment Key finding: L1 Digital Physiological dominates — confirming the AHN hypothesis that digital connectivity has assumed a foundational physiological role in human motivation. Search queries used:1. smartphone addiction anxiety disconnection2. nomophobia fear missing out digital3. digital detox cortisol stress4. AI replacing workers identity fear5. algorithmic manipulation social media belonging Files:- ahn_youtube_videos.csv: 50 unique videos metadata- ahn_youtube_comments.csv: 1,403 raw comments- ahn_analysis_v2.csv: AHN level annotation per comment Analysis: Python 3.12, Google Colaboratory, April 2026