The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.
Nonverbal Behaviors, Persuasion, and Credibility
Abstract
This study examined the relationships among nonverbal behaviors, dimensions of source credibility, and speaker persuasiveness in a public speaking context. Relevant nonverbal literature was organized according to a Brunswikian lens model. Nonverbal behavioral composites, grouped according to their likely proximal percepts, were hypothesized to significantly affect both credibility and persuasiveness. A sample of 60 speakers gave videotaped speeches that were judged on credibility and persuasiveness by classmates. Pairs of trained raters coded 22 vocalic, kinesic, and proxemic nonverbal behaviors evidenced in the tapes. Results confirmed numerous associations between nonverbal behaviors and attributions of credibility and persuasiveness. Greater perceived competence and composure were associated with greater vocal and facial pleasantness, with greater facial expressiveness contributing to competence perceptions. Greater sociability was associated with more kinesic/proxemic immediacy, dominance, and relaxation and with vocal pleasantness. Most of these same cues also enhanced character judgments. No cues were related to dynamism judgments. Greater perceived persuasiveness correlated with greater vocal pleasantness (especially fluency and pitch variety), kinesic/proxemic immediacy, facial expressiveness, and kinesic relaxation (especially high random movement but little tension). All five dimensions of credibility related to persuasiveness. Advantages of analyzing nonverbal cues according to proximal percepts are discussed.
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
Cites
Inference of attitudes from the posture, orientation, and distance of a communicator.
Mehrabian, A. (1968) · Journal of Consulting and Clinical Psychology · doi:10.1037/h0025906 · Cited by 259
Cited by
Burgoon, J. K., Bonito, J. A., Ramirez, A., Dunbar, N. E., Kam, K., & Fischer, J. (2002) · Journal of Communication · doi:10.1111/j.1460-2466.2002.tb02567.x · Cited by 400
Self-citationInteractivity in human–computer interaction: a study of credibility, understanding, and influence
Burgoon, J. K., Bonito, J. A., Bengtsson, B., Cederberg, C., Lundeberg, M., & Allspach, L. (2000) · Computers in Human Behavior · doi:10.1016/s0747-5632(00)00029-7 · Cited by 384
Self-citationBridging the Gap between Social Animal and Unsocial Machine: A Survey of Social Signal Processing
Vinciarelli, A., Pantic, M., Heylen, D., Pelachaud, C., Poggi, I., D'Errico, F., & Schroeder, M. (2012) · IEEE Transactions on Affective Computing · doi:10.1109/t-affc.2011.27 · Cited by 381
The impact of chatbot conversational skill on engagement and perceived humanness
Schuetzler, R. M., Grimes, G. M., & Scott Giboney, J. (2020) · Journal of Management Information Systems · doi:10.1080/07421222.2020.1790204 · Cited by 357
Burgoon, J. K., Bonito, J. A., Bengtsson, B., Ramirez, A., Dunbar, N. E., & Miczo, N. (1999) · Journal of Management Information Systems · doi:10.1080/07421222.1999.11518255 · Cited by 253
Self-citation
Metadata
- Authors
- BURGOON, J. K., BIRK, T., & PFAU, M.
- Venue
- Human Communication Research
- Publisher
- Oxford University Press (OUP)
- Published
- 1990-09
- Volume
- 17
- Issue
- 1
- Pages
- 140-169
- ISSN
- 0360-3989 (ISSN-L)
- 1468-2958
- OpenAlex
- W2023890289
- Cited by
- 395
- References
- 1
- FWCI
- 1.41
- 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: Nonverbal Behaviors, Persuasion, and Credibility. https://app.cochat.ai/papers/10.1111/j.1468-2958.1990.tb00229.x
- The paper
- BURGOON, J. K., BIRK, T., & PFAU, M. (1990). Nonverbal Behaviors, Persuasion, and Credibility. Human Communication Research. https://doi.org/10.1111/j.1468-2958.1990.tb00229.x
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.