Synthetic Resonant Amplification Framework Dataset (SRAF-200) and Seed Corpus (N=30) – Version 2

This dataset accompanies the article “Interrupting Resonant Amplification: A Mechanistic and Design Framework for Human–AI Interaction,” accepted for publication in Computers in Human Behavior Reports (2026). Contents: • SRAF_200_full_v2.csv – 200 fully synthetic dialogues labeled by RAF Phase (P1–P3) and Distortion Type. • SRAF_200_synthetic_v2.csv – simplified variant for linguistic-marker analysis (PCCI components). • SRAF_200_with_full_metadata_v2.csv – combined version with metadata fields. • RAF_MiniDataset_30entries_CleanEnglish.xlsx – public 30-excerpt seed corpus (construct grounding). • README_v2.txt, CODEBOOK_v2.md, MANIFEST_v2.json. Purpose: To support measurement development and audit prototyping for the Resonant Amplification Framework (RAF). Ethics: All texts are synthetic or paraphrased public excerpts; no personal data. Citation: Kim, R. S. (2025). Resonant Amplification Framework: Corpora and Supplementary Materials (Version 2) [Data set]. Zenodo. https://doi.org/10.5281/zenodo.17278678