Show simple item record

dc.contributor.authorBurgoon, J.K.
dc.contributor.authorWang, R.X.
dc.contributor.authorChen, X.
dc.contributor.authorGe, T.S.
dc.contributor.authorDorn, B.
dc.date.accessioned2022-03-18T00:03:51Z
dc.date.available2022-03-18T00:03:51Z
dc.date.issued2022
dc.identifier.citationBurgoon, J. K., Wang, R. X., Chen, X., Ge, T. S., & Dorn, B. (2022). How the Brunswikian Lens Model Illustrates the Relationship Between Physiological and Behavioral Signals and Psychological Emotional and Cognitive States. Frontiers in Psychology.
dc.identifier.issn1664-1078
dc.identifier.doi10.3389/fpsyg.2021.781487
dc.identifier.urihttp://hdl.handle.net/10150/663653
dc.description.abstractSocial relationships are constructed by and through the relational communication that people exchange. Relational messages are implicit nonverbal and verbal messages that signal how people regard one another and define their interpersonal relationships—equal or unequal, affectionate or hostile, inclusive or exclusive, similar or dissimilar, and so forth. Such signals can be measured automatically by the latest machine learning software tools and combined into meaningful factors that represent the socioemotional expressions that constitute relational messages between people. Relational messages operate continuously on a parallel track with verbal communication, implicitly telling interactants the current state of their relationship and how to interpret the verbal messages being exchanged. We report an investigation that explored how group members signal these implicit messages through multimodal behaviors measured by sensor data and linked to the socioemotional cognitions interpreted as relational messages. By use of a modified Brunswikian lens model, we predicted perceived relational messages of dominance, affection, involvement, composure, similarity and trust from automatically measured kinesic, vocalic and linguistic indicators. The relational messages in turn predicted the veracity of group members. The Brunswikian Lens Model offers a way to connect objective behaviors exhibited by social actors to the emotions and cognitions being perceived by other interactants and linking those perceptions to social outcomes. This method can be used to ascertain what behaviors and/or perceptions are associated with judgments of an actor’s veracity. Computerized measurements of behaviors and perceptions can replace manual measurements, significantly expediting analysis and drilling down to micro-level measurement in a previously unavailable manner. Copyright © 2022 Burgoon, Wang, Chen, Ge and Dorn.
dc.language.isoen
dc.publisherFrontiers Media S.A.
dc.rightsCopyright © 2022 Burgoon, Wang, Chen, Ge and Dorn. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY).
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/
dc.subjectaffection
dc.subjectdominance
dc.subjectinvolvement
dc.subjectnervousness
dc.subjectnonverbal communication
dc.subjectrelational communication
dc.subjectsimilarity
dc.subjecttrust
dc.titleHow the Brunswikian Lens Model Illustrates the Relationship Between Physiological and Behavioral Signals and Psychological Emotional and Cognitive States
dc.typeArticle
dc.typetext
dc.contributor.departmentCenter for the Management of Information, University of Arizona
dc.contributor.departmentManagement Information Systems, University of Arizona
dc.identifier.journalFrontiers in Psychology
dc.description.noteOpen access journal
dc.description.collectioninformationThis item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at repository@u.library.arizona.edu.
dc.eprint.versionFinal published version
dc.source.journaltitleFrontiers in Psychology
refterms.dateFOA2022-03-18T00:03:51Z


Files in this item

Thumbnail
Name:
fpsyg-12-781487.pdf
Size:
548.3Kb
Format:
PDF
Description:
Final Published Version

This item appears in the following Collection(s)

Show simple item record

Copyright © 2022 Burgoon, Wang, Chen, Ge and Dorn. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY).
Except where otherwise noted, this item's license is described as Copyright © 2022 Burgoon, Wang, Chen, Ge and Dorn. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY).