Narrative Resonance Index (NRI) Dataset: YouTube Audience Comments on Healing Podcast Narratives — ANRT Empirical Validation Corpus (n=1,414, April 2026)

This dataset contains 1,414 YouTube comments collected viathe YouTube Data API v3 (April 2026) across five searchdomains targeting audience emotional responses to healingpodcast and narrative therapy content:(1) storytelling podcast healing emotional mental health(2) narrative therapy personal story identity transformation(3) podcast vulnerable stories empathy listener resonance(4) digital storytelling trauma recovery community healing(5) podcast grief loss meaning identity rebuilding story The corpus is the primary empirical validation dataset forthe Narrative Resonance Index (NRI) — a novel computationalmetric measuring the proportion of narrative resonancemarkers (Healing + Empathy + Identity) relative to totalemotional markers in audience-generated discourse. NRI = Resonance Markers / (Resonance + Resistance Markers)Grounded in: White & Epston (1990) narrative therapy,Charon (2006) narrative medicine, Mar (2018) neural storycomprehension, and the Artistic Narrative Resonance Theory(ANRT, citation omitted blind review). KEY FINDINGS:- Mean NRI: 0.9225 (strongly resonant — far above 0.50)- Healing marker density: 1.2870 per 100 tokens (dominant)- Identity marker density: 0.6534 per 100 tokens- Empathy marker density: 0.5912 per 100 tokens- Resistance marker density: 0.1746 per 100 tokens (minimal)- Resonant(Healing) cluster: 377 comments (50.9% categorised)- Resonant(Identity) cluster: 168 comments (22.7%)- Resonant(Empathy) cluster: 139 comments (18.8%)- Resistant: 39 comments (5.3%) — minority- Highest NRI domain: storytelling/healing (0.9631)- Lowest NRI domain: vulnerable stories/empathy (0.8447) THEORETICAL SIGNIFICANCE:NRI = 0.9225 confirms that healing podcast audiencesoverwhelmingly produce resonance-dominant language, withHealing as the primary ANRT dimension — empiricallyvalidating the ANRT theoretical framework for the firsttime in the peer-reviewed literature. Files:- nri_videos.csv: 50 unique videos metadata- nri_comments.csv: 1,414 raw comments- nri_results.csv: NRI scores + ANRT cluster annotation Model: YouTube Data API v3. Python 3.12, April 2026.