A System for Multi-person, Multi-modal Data Collection in Behavioral Information Systems

Dorn, Bradley; Dunbar, Norah E.; Burgoon, Judee K.; Nunamaker, Jay F.; Giles, Matt; Walls, Brad; Chen, Xunyu; Wang, Xinran; Ge, Saiying; Subrahmanian, V. S.

doi:10.1007/978-3-030-54383-9_4

Cited by 5 publications

(3 citation statements)

References 3 publications

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“…We devised a method for analyzing trust using an interactive social game created by Don Eskridge called The Resistance (variations of the game are sometimes known as Mafia or Werewolf) played in groups comprised of five to eight strangers. A detailed description of the game is found in [24]. It began with an ice-breaker activity designed to establish a baseline for perceptions of dominance, liking,…”

Section: Methodsmentioning

confidence: 99%

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The Psychology of Trust from Relational Messages

Burgoon¹,

Dunbar²,

Metzger³

et al. 2023

The Psychology of Trust

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A fundamental underpinning of all social relationships is trust. Trust can be established through implicit forms of communication called relational messages. A multidisciplinary, multi-university, cross-cultural investigation addressed how these message themes are expressed and whether they are moderated by culture and veracity. A multi-round decision-making game with 695 international participants assessed the nonverbal and verbal behaviors that express such meanings as affection, dominance, and composure, from which people ultimately determine who can be trusted and who not. Analysis of subjective judgments showed that trust was most predicted by dominance, then affection, and lastly, composure. Behaviorally, several nonverbal and verbal behaviors associated with these message themes were combined to predict trust. Results were similar across cultures but moderated by veracity. Methodologically, automated software extracted facial features, vocal features, and linguistic metrics associated with these message themes. A new attentional computer vision method retrospectively identified specific meaningful segments where relational messages were expressed. The new software tools and attentional model hold promise for identifying nuanced, implicit meanings that together predict trust and that can, in combination, serve as proxies for trust.

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Section: Methodsmentioning

confidence: 99%

“…Additionally, players won monetary rewards by being voted as a leader or winning the game. (See [24] for more details).…”

Section: Methodsmentioning

confidence: 99%

The Psychology of Trust from Relational Messages

Burgoon¹,

Dunbar²,

Metzger³

et al. 2023

The Psychology of Trust

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“…A detailed description of the game is found in Dorn et al (2021). An ice-breaker activity introducing one another established a baseline for players' behaviors and perceptions of one another.…”

Section: Methodsmentioning

confidence: 99%

How the Brunswikian Lens Model Illustrates the Relationship Between Physiological and Behavioral Signals and Psychological Emotional and Cognitive States

et al. 2022

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Social 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.

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