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American English Genre and Rhetoric Analysis
Data Science and Analytics
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About
provides metadata and linguistic feature analysis derived from the widely used COCA corpus. It facilitates the study of English language evolution, genre distinctions, and rhetorical strategies over a thirty-year period. By quantifying elements such as expert vocabulary, citation styles, and confidence markers, it supports research in linguistics, education, and natural language processing.
Columns
- text_id: Unique identifier for the text segment.
- text_type: The primary category of the text (e.g., ACAD for Academic).
- sub_type: Sub-categorisation of the text genre (e.g., Arg for Argumentative).
- year: The year of publication, ranging from 1990 to 2019.
- word_count: The total number of words in the specific text segment.
- Character Types: Metric indicating the diversity or nature of characters used.
- Citation Authority: Score measuring reliance on authoritative citations.
- Citation Controversy: Metric assessing the presence of controversial citations.
- Citation Hedged: Quantification of hedged or cautious citation usage.
- Citation Neutral: Measure of neutral citation phrasing.
- Confidence Hedged: Metric indicating tentative or hedged expressions of confidence.
- Confidence High: Score reflecting high-confidence language.
- Confidence Low: Score reflecting low-confidence or uncertain language.
- Expert Vocabulary: Quantification of specialised or domain-specific terminology.
- Information Comparison: Metric evaluating comparative information structures.
- Information Quantities: Measurement of quantitative information presentation.
- Methods Results Discussion: Score related to the structural elements of academic discourse (methods, results, discussion).
- Purpose Plan: Metric assessing the articulation of purpose or planning in the text.
- Reader Directed Metadiscourse: Measure of language explicitly guiding the reader.
- Reader Directed Metadiscourse FP: Specific metric for reader-directed metadiscourse (First Person focus).
- Reasoning: Quantifiable score of reasoning or argumentative logic present in the text.
Distribution
- Format: Tabular data (CSV).
- Size: 4.77 MB.
- Structure: 42,700 valid records with 21 columns.
- Data Integrity: 100% valid entries with no missing or mismatched data found in the sample analysis.
Usage
- Linguistic Research: Analysing shifts in American English vocabulary and grammar over time.
- Academic Writing Studies: Investigating rhetorical moves (citations, hedging, confidence) across different academic disciplines.
- Genre Analysis: Comparing stylistic features between fiction, news, and academic texts.
- Natural Language Processing: Training models to recognise genre-specific attributes or sentiment confidence.
Coverage
- Geographic Scope: United States (American English).
- Time Range: 1990 to 2019.
- Genres: Spoken, Fiction, Popular Magazines, Newspapers, Academic Texts, TV/Movies, Blogs, Web Pages.
License
CC0: Public Domain
Who Can Use It
- Linguists: For corpus linguistics and diachronic studies.
- Educators: Developing materials based on real-world usage of academic or spoken English.
- Data Scientists: For text classification and NLP feature engineering.
- Students: conducting beginner to advanced research in English language studies.
Dataset Name Suggestions
- COCA Linguistic Metrics and Metadata 1990-2019
- American English Genre and Rhetoric Analysis
- Corpus of Contemporary American English Feature Set
- 30-Year English Language Variation Metrics
Attributes
Original Data Source: American English Genre and Rhetoric Analysis
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