62 academic English linguistic features were identified and analyzed to develop a multidimensional analysis model for distinguishing native English and Chinese researchers' writing. The dataset, created by Jiaqi Deng and last updated in April 2026, is stored in an XLS file of 5.5 KB. It yielded four interpretable dimensions describing stylistic differences in academic involvement, argumentation, evaluation, and reporting style.
Use Cases
- Training models to classify academic writing style based on identified linguistic features.
- Comparing linguistic patterns between native and non-native English research articles.
- Developing novel MDA frameworks for specific academic genres based on the proposed tagging method.
Strengths
- Defines 62 specific linguistic features for academic writing analysis.
- Derives four interpretable dimensions from the feature analysis.
- Uses a CC-BY-4.0 license, allowing for broad reuse and adaptation.
Limitations
- Row count is unknown, which may limit suitability assessment.
- Column-level documentation is absent; field semantics must be inferred after download.
- The dataset is very small at 5.5 KB, indicating limited scope.
Provenance
- Source
- Jiaqi Deng
- Collection Method
- Features were tagged with an MDA tagger and counted by PatCount software.
- Time Range
- null
- Freshness
- Last updated 2026-04-24 17:27:59; freshness should be verified.
- Geography
- null