userderived

Userderived refers to data, metrics, or content that are derived from user interactions, attributes, or historical behavior rather than being explicitly created by the user. It is often used in data pipelines, analytics, and machine learning to describe features or outputs that summarize or infer user state.

Common examples include engineered features such as engagement affinity scores, propensity to convert, or churn risk, which are computed from logs of page views, clicks, purchases, and time spent. Personalized recommendations, risk assessments, and segmentation labels can also be considered userderived when produced automatically from user data.

It is distinct from user-generated content, which is content created directly by users (posts, reviews, uploads). It is also distinct from derived data about a user created by analysts, though in practice the line can blur when analysts produce new summaries.

Because it relies on sensitive user data, governance considerations include consent, data minimization, and privacy-preserving techniques such as anonymization and differential privacy. Transparency about what is derived and how it is used is a growing concern.

See also: user data, user-generated content, data derivation, feature engineering, privacy-preserving data analysis.