ArticleScientific data2026
Coding and Validation for Breadth and Desirability of 1,214 English Adjectives.
Article in Scientific data, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
1 citing paper in PubMed.
- Coding and Validation for Breadth and Desirability of 1,214 English Adjectives.Scientific data · 2026Article
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Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Adjectives are essential in how people describe, evaluate, and reason about others. They differ along meaningful semantic dimensions such as desirability (e.g., "friendly" is more positive than "rude") and breadth (e.g., "punctual" is narrower than "reliable"). Adjectival breadth has received limited empirical attention, partly because existing resources are sparse and outdated. We introduce a new database with subjective ratings from approximately 1,500 Americans for 1,214 adjectives on both breadth and desirability. Unlike existing resources, this updated database is more comprehensive and diverse, allowing for detailed analysis of adjectival use in academic and applied contexts. We validate this database with a large-scale analysis of online product reviews, showing how variation in adjective breadth is a common feature of natural language use. This database should prove valuable for research on semantic representation, social inference, and evaluative communication across various fields.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.