The DOI matches its Crossref record.
Representativeness in Corpus Design
Abstract
The present paper addresses a number of issues related to achieving ‘representativeness’ in linguistic corpus design, including: discussion of what it means to ‘represent’ a language, definition of the target population, stratified versus proportional sampling of a language, sampling within texts, and issues relating to the required sample size (number of texts) of a corpus. The paper distinguishes among various ways that linguistic features can be distributed within and across texts; it analyses the distributions of several particular features, and it discusses the implications of these distributions for corpus design. The paper argues that theoretical research should be prior in corpus design, to identify the situational parameters that distinguish among texts in a speech community, and to identify the types of linguistic features that will be analysed in the corpus. These theoretical considerations should be complemented by empirical investigations of linguistic variation in a pilot corpus of texts, as a basis for specific sampling decisions. The actual construction of a corpus would then proceed in cycles: the original design based on theoretical and pilot-study analyses, followed by collection of texts, followed by further empirical investigations of linguistic variation and revision of the design.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cited by
Coxhead, A. (2000) · TESOL Quarterly · doi:10.2307/3587951 · Cited by 2,780
Applying LDA Topic Modeling in Communication Research: Toward a Valid and Reliable Methodology
Maier, D., Waldherr, A., Miltner, P., Wiedemann, G., Niekler, A., Keinert, A., Pfetsch, B., Heyer, G., Reber, U., Häussler, T., et al. (2018) · Communication Methods and Measures · doi:10.1080/19312458.2018.1430754 · Cited by 832
Biber, D., & Conrad, S. (2019) · Cambridge University Press eBooks · doi:10.1017/9781108686136 · Cited by 623
Self-citationThe Oxford Handbook of Information Structure
(2016) · Oxford University Press eBooks · doi:10.1093/oxfordhb/9780199642670.001.0001 · Cited by 423
Argument Structure in Usage-Based Construction Grammar: Experimental and corpus-based perspectives
Perek, F. (2015) · Constructional Approaches to Language · doi:10.1075/cal.17 · Cited by 417
Metadata
- Authors
- BIBER, D.
- Venue
- Literary and Linguistic Computing
- Publisher
- Oxford University Press (OUP)
- Published
- 1993-10-01
- Volume
- 8
- Issue
- 4
- Pages
- 243-257
- ISSN
- 0268-1145 (ISSN-L)
- 1477-4615
- OpenAlex
- W2148259819
- Cited by
- 1,269
- References
- 0
- FWCI
- 1.48
- Type
- journal article
- Language
- en
- Open access
- closed
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: Representativeness in Corpus Design. https://app.cochat.ai/papers/10.1093/llc/8.4.243
- The paper
- BIBER, D. (1993). Representativeness in Corpus Design. Literary and Linguistic Computing. https://doi.org/10.1093/llc/8.4.243
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.