Reviewer Profiling Framework for Online Retail Platforms

A framework for profiling reviewer behavior on online retail platforms, comparing approaches to balance scalability and interpretability. The dataset was authored by Luisa Stracqualursi and last updated on March 25, 2026. It is a 5.5 KB XLS file shared under a CC-BY-4.0 license.

Use Cases

• Monitor reviewer behavior based on the described framework for profiling.
• Analyze extreme ratings based on the Reviewer Extremeness Index and Reviewer Polarity Index mentioned in the platform tags.
• Provide deeper insight into reviewer motivations based on the concept of nuanced interpretation of historical extreme behaviors.
• Develop a scalable tool for platform moderation based on the described complementary indices for profiling.

Strengths

• Dataset is small (5.5 KB), facilitating quick download and inspection.
• Explicitly licensed for open use under CC-BY-4.0.
• Last update date is precisely recorded as 2026-03-25 17:44:52.

Limitations

• Row count is unknown, which may limit suitability assessment.
• Column-level documentation is absent; field semantics must be inferred after download.
• Description metadata is limited; actual data quality requires manual inspection after download.

Provenance

Source

figshare, authored by Luisa Stracqualursi.

Collection Method

Method of data gathering is not described.

Time Range

Temporal coverage is not specified.

Freshness

Last updated 2026-03-25 17:44:52; freshness should be verified.

Geography

Spatial coverage is not specified.