Human and AI Authorship Effects on Relational Perceptions and Message Evaluations

Data for a project investigating the self-effects of AI-mediated communication. The dataset likely contains variables related to human and AI authorship, relational meta-perceptions, message evaluations, and linguistic markers of expressive writing. It was authored by Jorge Pena and published on the Harvard Dataverse platform, with a last update recorded on 2026-04-28.

Use Cases

• Analyzing how perceived authorship (human vs. AI) influences message evaluations (inferred from domain, verify after download)
• Modeling the relationship between linguistic markers and relational perceptions in written communication (inferred from domain, verify after download)
• Training classifiers to distinguish between human and AI-authored expressive writing based on linguistic features (inferred from domain, verify after download)

Strengths

• Published on the Harvard Dataverse platform, a reputable academic repository.
• Authored by a named researcher (Jorge Pena), providing traceability.
• Last updated on 2026-04-28 14:39:23, indicating recent maintenance.

Limitations

• Metadata is minimal; actual content requires verification after download.
• Column-level documentation is absent; field semantics must be inferred after download.
• Row count, file formats, and license information are unknown, which may limit suitability assessment.

Provenance

Source

Harvard Dataverse

Freshness

Last updated 2026-04-28 14:39:23; freshness should be verified.