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A Systems Model of Dyadic Nonverbal Interaction

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Abstract

This article discusses a new systems model of dyadic nonverbal interaction. The model builds on earlier theories by integrating partners’ parallel sending and receiving nonverbal processes into a broader, dynamic ecological system. It does so in two ways. First, it moves the level of description beyond the individual level to the coordination of both partners’ contributions to the interaction. Second, it recognizes that the relationships between (a) individuals’ characteristics and processes and (b) the social ecology of the interaction setting are reciprocal and best analyzed at the systems level. Thus, the systems model attempts to describe and explain the dynamic interplay among individual, dyadic, and environmental processes in nonverbal interactions. The potential utility and the limitations of the systems model are discussed and the implications for future research considered. Although the systems model is focused explicitly on face-to-face nonverbal communication, it has considerable relevance for digital communication. Specifically, this model provides a useful framework for examining the social effects of mobile device use and as a template for studying human–robot interactions.

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References

  • Altman, I. (1975). The environment and social behavior. Monterey, CA: Brooks/Cole.

    Google Scholar 

  • Ambady, N., Bernieri, F. J., & Richeson, J. A. (2000). Toward a histology of social behavior: Judgmental accuracy from thin slices of the behavioral stream. In M. P. Zanna (Ed.), Advances in experimental social psychology (Vol. 32, pp. 201–271). San Diego, CA: Academic Press.

    Google Scholar 

  • Ambady, N., & Rosenthal, R. (1992). Thin slices of behavior as predictors of interpersonal consequences: A meta-analysis. Psychological Bulletin, 111, 256–274.

    Article  Google Scholar 

  • Argyle, M., & Dean, J. (1965). Eye-contact, distance and affiliation. Sociometry, 28, 289–304.

    Article  Google Scholar 

  • Bargh, J. A. (1989). Conditional automaticity: Varieties of automatic influence in social perception and cognition. In J. S. Uleman & J. A. Bargh (Eds.), Unintended thought (pp. 3–51). New York: Guilford.

    Google Scholar 

  • Bargh, J. A. (1990). Auto-motives: Preconscious determinants of thought and behavior. In E. T. Higgins & R. M. Sorrentino (Eds.), Handbook of motivation and cognition (2nd ed., pp. 93–130). New York: Guilford.

    Google Scholar 

  • Bargh, J. A. (1997). The automaticity of everyday life. In R. S. Wyer (Ed.), Advances in social cognition (pp. 1–61). Mahwah, NJ: Lawrence Erlbaum Associates.

    Google Scholar 

  • Bargh, J. A., Chen, M., & Burrows, L. (1996). Automaticity of social behavior: direct effects of trait construct and stereotype activation on action. Journal of Personality and Social Psychology, 71, 230–244.

    Article  Google Scholar 

  • Bargh, J. A., Gollwitzer, P. M., Lee-Chai, A., Barndollar, K., & Trotschel, R. (2001). The automated will: nonconscious activation and pursuit of behavioral goals. Journal of Personality and Social Psychology, 81, 1014–1027.

    Article  Google Scholar 

  • Barker, R. G. (1968). Ecological psychology: Concepts and methods for studying the environment of human behavior. Stanford, CA: Stanford University Press.

    Google Scholar 

  • Baumeister, R. F., Vohs, K. D., & Funder, D. C. (2007). Psychology as the science of self-reports and finger movements. Whatever happened to actual behavior? Perspectives on Psychological Science, 2, 396–403.

    Article  Google Scholar 

  • Berger, C. B. (1997). Planning strategic interaction. Mahwah, NJ: Erlbaum.

    Google Scholar 

  • Bilton, N. (2013). Disruptions: More connected, yet more alone. The New York Times. Retrieved September 22, 2013, from http://bits.blogs.nytimes.com/2013/09/01/disruptions-more-connected-yet-more-alone/?_r=1.

  • Breazeal, C. (2003). Emotion and sociable humanoid robots. International Journal of Human-Computer Studies, 59, 119–155.

    Article  Google Scholar 

  • Brunswik, E. (1955). Representative design and probabilistic theory in a functional psychology. Psychological Review, 62, 193–217.

    Article  Google Scholar 

  • Bugeja, M. (2005). Interpersonal divide: The search for community in a technological age. New York: Oxford University Press.

    Google Scholar 

  • Burgoon, J. K. (1978). A communication model of personal space violations: Explication and an initial test. Human Communication Research, 4, 129–142.

    Article  Google Scholar 

  • Burgoon, J. K., Stern, L. A., & Dillman, L. (1995). Interpersonal adaptation: Dyadic interaction patterns. New York: Cambridge University Press.

    Book  Google Scholar 

  • Cappella, J. N., & Greene, J. O. (1982). A discrepancy-arousal explanation of mutual influence in expressive behavior for adult and infant-adult interaction. Communication Monographs, 49, 89–114.

    Article  Google Scholar 

  • Carney, D. A., Colvin, C. A., & Hall, J. A. (2007). A thin slice perspective on the accuracy of first impressions. Journal of Research in Personality, 41, 1054–1072.

    Article  Google Scholar 

  • Chartrand, T. Y., & Bargh, J. A. (1999). The chameleon effect: The perception-behavior link and social interaction. Journal of Personality and Social Psychology, 76, 893–910.

    Article  Google Scholar 

  • Cloutier, J., & Macrae, C. N. (2007). Who or what are you? Facial orientation and person construal. European Journal of Social Psychology, 37, 1298–1309.

    Article  Google Scholar 

  • Corrales, J., Gomez, G., Torres, F., & Perdereau, V. (2012). Cooperative tasks between humans and robots in industrial environments. International Journal of Advanced Robotic Systems, 9, 1–10.

    Article  Google Scholar 

  • Crivelli, C., & Fridlund, A. J. (2018). Facial displays are tools for social influence. Trends in Cognitive Sciences, 22, 388–399.

    Article  Google Scholar 

  • Dautenhahn, K. (2002). Design spaces and niche spaces of believable social robots. In Proceedings of the 2002 IEEE Robot and Human Interactive Communication (pp. 192–197).

  • De Sola Gutierrez, J., De Fonseca, F. R., & Rubio, G. (2016). Cell phone addiction: A review. Frontiers in Psychiatry, 7, 175.

    Google Scholar 

  • Dijksterhuis, A., & Bargh, J. A. (2001). The perception-behavior expressway: Automatic effects of social perception on social behavior. In M. P. Zanna (Ed.), Advances in experimental social psychology (Vol. 33, pp. 1–40). San Diego: Academic Press.

    Google Scholar 

  • Ekman, P. (1999). Basic emotions. In T. D. T. Power (Ed.), The handbook of cognition and emotion (pp. 45–60). Sussex: Wiley.

    Google Scholar 

  • Fiske, S. T. (1992). Thinking is for doing: Portraits of social cognition from daguerreotype to laserphoto. Journal of Personality and Social Psychology, 63, 877–889.

    Article  Google Scholar 

  • Fiske, S. T., & Taylor, S. E. (1995). Social cognition (2nd ed.). New York: McGraw-Hill.

    Google Scholar 

  • Fridlund, A. J. (1994). Human facial expression: An evolutionary view. San Diego: Academic Press.

    Google Scholar 

  • Fridlund, A. J. (2017). The behavioral ecology view of facial expressions, 25 years later. In J. M. Fernandez-Dols & J. A. Russell (Eds.), The science of facial expressions (pp. 77–92). Oxford: Oxford University Press.

    Google Scholar 

  • Gilbert, D. T., & Krull, D. S. (1988). Seeing less and knowing more: The benefits of perceptual ignorance. Journal of Personality and Social Psychology, 54, 193–202.

    Article  Google Scholar 

  • Goffman, E. (1963). Behavior in public places. New York: Free Press.

    Google Scholar 

  • Goodrich, M., & Schultz, A. (2007). Human-robot interaction: A survey. Foundations and Trends in Human-Computer Interaction, 1, 203–275.

    Article  Google Scholar 

  • Gosling, S. D., Gaddis, S., & Vazire, S. (2008). First impressions based on the environments we create and inhabit. In N. Ambady & J. J. Skowronski (Eds.), First impressions (pp. 334–356). New York: Guilford.

    Google Scholar 

  • Hall, J. A., & Knapp, M. L. (Eds.). (2013). Nonverbal communication. Berlin: DeGruyter Mouton.

    Google Scholar 

  • Hugenberg, K., & Bodenhausen, G. V. (2003). Facing prejudice: Implicit prejudice and the perception of facial threat. Psychological Science, 14, 640–643.

    Article  Google Scholar 

  • James, W. (1983). The principles of psychology. Cambridge, MA: Harvard University Press. (Original work published 1890).

  • Jones, E. E., & Davis, K. E. (1965). From acts to dispositions: The attribution process in person perception. In L. Berkowitz (Ed.), Advances in experimental social psychology (Vol. 2, pp. 220–266). New York: Academic Press.

    Google Scholar 

  • Kelley, H. H. (1967). Attribution theory in social psychology. In D. Levine (Ed.), Nebraska symposium on motivation (Vol. 15, pp. 192–238). Lincoln, NE: University of Nebraska Press.

    Google Scholar 

  • Knowles, E. S. (1983). Social physics and the effects of others: Tests of the effects of audience size and distance on social judgments and behavior. Journal of Personality and Social Psychology, 45, 1263–1279.

    Article  Google Scholar 

  • Lakin, J. L. (2006). Automatic cognitive processes and nonverbal communication. In V. Manusov & M. L. Patterson (Eds.), The Sage handbook of nonverbal communication (pp. 59–77). Thousand Oaks, CA: Sage Publications.

    Chapter  Google Scholar 

  • Lakin, J. L. (2013). Behavioral mimicry and interpersonal synchrony. In J. A. Hall & M. L. Knapp (Eds.), Nonverbal communication (pp. 539–575). Berlin: De Gruyter Mouton.

    Google Scholar 

  • Lederman, T., & Kenny, D. A. (2017). Analyzing dyadic data with multilevel modeling versus structural equation modeling: A tale of two methods. Journal of Family Psychology, 31, 442–452.

    Article  Google Scholar 

  • Leung, L., & Liang, J. (2015). Mobile phone addiction. In Z. Yan (Ed.), Encyclopedia of mobile phone behavior (pp. 640–647). Hershey, PA: IGI Global Publishers.

    Chapter  Google Scholar 

  • Liljenquist, K. A., Zhong, C.-B., & Galinsky, A. D. (2010). The smell of virtue: Clean scents promote reciprocity and charity. Psychological Science, 21(381–383), 21.

    Google Scholar 

  • Lloyd, D. M., Coates, A., Knopp, J., Oram, S., & Rowbotham, S. (2009). Don’t stand so close to me: The effect of auditory input on interpersonal space. Perception, 38, 617–620.

    Article  Google Scholar 

  • Loersch, C., & Payne, B. K. (2011). The situated inference model: An integrative account of the effects of primes on perception, behavior, and motivation. Perspectives on Psychological Science, 6, 234–252.

    Article  Google Scholar 

  • Manusov, V., & Patterson, M. L. (Eds.). (2006). The Sage handbook of nonverbal communication. Thousand Oaks, CA: Sage.

    Google Scholar 

  • Marquardt, G., Cross, E. S., de Sousa, A. A., Edelstein, E., Farne, A., Leszczynski, M., et al. (2015). There or not there? A multidisciplinary review and research agenda on the impact of transparent barriers on human perception, action, and social behavior. Frontiers in Psychology, 6, 1381. https://doi.org/10.3389/fpsyg.2015.0138.

    Article  PubMed  PubMed Central  Google Scholar 

  • Matsumoto, D., Hwang, H. C., & Frank, M. G. (Eds.). (2016). APA handbook of nonverbal communication. Washington, DC: American Psychological Association.

    Google Scholar 

  • Mavridis, N. (2014). A review of verbal and non-verbal human-robot interactive communication. Robotics and Autonomous System, 63, 22–35.

    Article  Google Scholar 

  • McArthur, L. Z., & Baron, R. M. (1983). Toward an ecological theory of social perception. Psychological Review, 90, 215–238.

    Article  Google Scholar 

  • Oishi, S., & Graham, J. (2010). Social ecology: Lost and found in psychological science. Perspectives on Psychological Science, 5, 356–377.

    Article  Google Scholar 

  • Park, S., Patterson, M. L., & Hwang, Y. (2015). Toward a systems model of human-robot interaction. Unpublished manuscript.

  • Patterson, M. L. (1973). Compensation in nonverbal immediacy behaviors: A review. Sociometry, 36, 237–252.

    Article  Google Scholar 

  • Patterson, M. L. (1976). An arousal model of interpersonal intimacy. Psychological Review, 83, 237–252.

    Article  Google Scholar 

  • Patterson, M. L. (1982). A sequential functional model of nonverbal exchange. Psychological Review, 89, 231–249.

    Article  Google Scholar 

  • Patterson, M. L. (1983). Nonverbal behavior: A functional perspective. New York: Springer.

    Book  Google Scholar 

  • Patterson, M. L. (1995). A parallel process model of nonverbal communication. Journal of Nonverbal Behavior, 19, 3–29.

    Article  Google Scholar 

  • Patterson, M. L. (2001). Toward a comprehensive model of nonverbal communication. In W. P. Robinson & H. Giles (Eds.), The new handbook of language and social psychology (pp. 159–176). Chichester: Wiley.

    Google Scholar 

  • Patterson, M. L. (2006). The evolution of theories of nonverbal interaction. In V. Manusov & M. L. Patterson (Eds.), The Sage handbook of nonverbal communication (pp. 21–39). Thousand Oaks, CA: Sage.

    Chapter  Google Scholar 

  • Patterson, M. L. (2008). Back to social behavior: Mining the mundane. Basic and Applied Social Psychology, 30, 93–101.

    Article  Google Scholar 

  • Patterson, M. L. (2011). More than words: The power of nonverbal communication. Barcelona: Editorial Aresta.

    Google Scholar 

  • Patterson, M. L. (2013). Toward a systems approach to nonverbal interaction. In J. A. Hall & M. L. Knapp (Eds.), Nonverbal communication (pp. 515–538). Berlin: DeGruyter Mouton.

    Google Scholar 

  • Patterson, M. L. (2014). Reflections on historical trends and prospects in contemporary nonverbal research. Journal of Nonverbal Behavior, 38, 171–180.

    Article  Google Scholar 

  • Patterson, M. L., Lammers, V. M., & Tubbs, M. E. (2014). Busy signal: Effects of mobile device usage on pedestrian encounters. Journal of Nonverbal Behavior, 38, 313–324.

    Article  Google Scholar 

  • Patterson, M. L., & Quadflieg, S. (2016). The physical environment and nonverbal communication. In D. Matsumoto, H. C. Hwang, & M. G. Frank (Eds.), APA handbook of nonverbal communication (pp. 189–220). Washington, DC: American Psychological Association.

    Chapter  Google Scholar 

  • Patterson, M. L., & Ritts, V. (1997). Social and communicative anxiety: A review and meta-analysis. In B. R. Burleson (Ed.), Communication Yearbook 20 (pp. 262–303). Thousand Oaks, CA: Sage Publications.

    Google Scholar 

  • Patterson, M. L., Webb, A., & Schwartz, W. (2002). Passing encounters: Patterns of recognition and avoidance in pedestrians. Basic and Applied Social Psychology, 24, 57–66.

    Article  Google Scholar 

  • Re, D. E., & Rule, N. O. (2016). Appearance and physiognomy. In D. Matsumoto, H. C. Hwang, & M. G. Frank (Eds.), APA handbook of nonverbal communication (pp. 221–256). Washington, DC: American Psychological Association.

    Chapter  Google Scholar 

  • Rizzolatti, G., & Craighero, L. (2004). The mirror-neuron system. Annual Review of Neuroscience, 27, 169–192.

    Article  Google Scholar 

  • Schachter, S., & Singer, J. E. (1962). Cognitive, social, and physiological determinants of emotional state. Psychological Review, 69, 379–399.

    Article  Google Scholar 

  • Shanahan, M. J., Hill, P. L., Roberts, B. W., Eccles, J., & Friedman, H. S. (2014). Conscientiousness, health, and aging: The life course of personality model. Developmental Psychology, 50, 1407–1425.

    Article  Google Scholar 

  • Stokols, D. (2018). Social ecology in the digital age: Solving complex problems in a globalized world. London: Academic Press.

    Google Scholar 

  • Webb, E., Campbell, D., Schwartz, R., & Sechrest, L. (1966). Unobtrusive measures: Nonreactive research in the social sciences. Chicago: Rand McNally.

    Google Scholar 

  • Weir, K. (2018). The dawn of social robots. Monitor on Psychology, 49, 50–56.

    Google Scholar 

  • Wicker, A. W. (1979). An introduction to ecological psychology. Monterey, CA: Brooks/Cole.

    Google Scholar 

  • Zebrowitz, L. A. (1997). Reading faces: Window to the soul?. Boulder, CO: Westview Press.

    Google Scholar 

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  1. Department of Psychological Sciences, University of Missouri-St. Louis, One University Boulevard, St. Louis, MO, 63121-4400, USA

    Miles L. Patterson

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I am very grateful to Alan Fridlund, Judy Hall, and Howard Friedman for their careful reading of an earlier draft of the manuscript. Their insightful comments and questions, and more than a few corrections, improved the manuscript.

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Patterson, M.L. A Systems Model of Dyadic Nonverbal Interaction. J Nonverbal Behav 43, 111–132 (2019). https://doi.org/10.1007/s10919-018-00292-w

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