Student or educator? Sign up with your school email and get 6 months of Pro free.
Cited by 176

The DOI matches its Crossref record.

Discourse-Based Word Anticipation During Language Processing: Prediction or Priming?

Open access
Otten, Marte, Van Berkum, Jos J. A.·2008·Discourse Processes

Abstract

Language is an intrinsically open-ended system. This fact has led to the widely shared assumption that readers and listeners do not predict upcoming words, at least not in a way that goes beyond simple priming between words. Recent evidence, however, suggests that readers and listeners do anticipate upcoming words “on the fly” as a text unfolds. In 2 event-related potentials experiments, this study examined whether these predictions are based on the exact message conveyed by the prior discourse or on simpler word-based priming mechanisms. Participants read texts that strongly supported the prediction of a specific word, mixed with non-predictive control texts that contained the same prime words. In Experiment 1A, anomalous words that replaced a highly predictable (as opposed to a non-predictable but coherent) word elicited a long-lasting positive shift, suggesting that the prior discourse had indeed led people to predict specific words. In Experiment 1B, adjectives whose suffix mismatched the predictable noun's syntactic gender elicited a short-lived late negativity in predictive stories but not in prime control stories. Taken together, these findings reveal that the conceptual basis for predicting specific upcoming words during reading is the exact message conveyed by the discourse and not the mere presence of prime words.

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.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1080/01638530802356463

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.

A few free checks a day · papers already verified open instantly · results are public

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

See all 176

Metadata

Authors
Otten, M., & Van Berkum, J. J. A.
Venue
Discourse Processes
Published
2008-11-11
Volume
45
Issue
6
Pages
464-496
ISSN
  • 0163-853X (ISSN-L)
  • 1532-6950
OpenAlex
W2136646664
Cited by
176
References
0
FWCI
8.72
Type
journal article
Language
en
Open access
green

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: Discourse-Based Word Anticipation During Language Processing: Prediction or Priming? https://app.cochat.ai/papers/10.1080/01638530802356463
The paper
Otten, M., & Van Berkum, J. J. A. (2008). Discourse-Based Word Anticipation During Language Processing: Prediction or Priming? Discourse Processes. https://doi.org/10.1080/01638530802356463

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.