When the digital commons freeze: how perceived AI information misuse drives visual creators' defensive withdrawal through resource erosion — data and analysis code

Survey data and analysis code for a study of how visual creators respond toperceived misuse of their work as training data for generative AI. Cross-sectional survey of 513 visual creators publishing original work onpublic platforms, collected in September 2026. Nine constructs measured with33 seven-point Likert items. Analysed through PLS-SEM, an artificial neuralnetwork and necessary condition analysis. Files: full sample (N = 550, with exclusion flag), analysis sample (N = 513),latent variable scores, codebook with English and Chinese item wording andscale sources, and R scripts for the neural network and necessary conditionanalysis. See README.md for details. The files contain no direct or indirect identifiers.