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Cognitive modeling of socially transmitted affordances: a computational model of behavioral adoption tested against archival data from the Stanford Prison Experiment

  • SI BRIMS 2012
  • Published:
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Abstract

Social learning and adoption of new affordances govern the rise of new a variety of behaviors, from actions as mundane as dance steps to those as dangerous as new ways to make improvised explosive device (IED) detonators. Traditional diffusion models and social network structures fail to adequately explain who would be likely to imitate new behavior and why some agents adopt the behavior while others do not. To address this gap, a cognitive model was designed that represents well-known socio-cognitive factors of attention, social influence, and motivation that influence learning and adoption of new behavior. This model was implemented in the Performance Moderator Function Server (PMFServ) agent-based cognitive architecture, enabling the creation of simulations where affordances spread memetically through cognitive mechanisms. This approach models facets of behavioral adoption that have not been explored by existing architectures: unintentional learning, multi-layered social and environmental attention cues, and contextual adoption. To examine the effectiveness of this model, its performance was tested against data from the Stanford Prison Experiment collected from the Archives of the History of American Psychology.

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Notes

  1. In some prior publications, GSP Congruence has been expressed in terms of its complement (e.g., without the leading “1-”). This prior convention has occasionally caused confusion, as low values meant high congruence. Equation (3) amends the expression so that 0 is the lowest congruence and 1 is the highest congruence.

References

  • Adomo TW, Frenkel-Brunswik E, Levinson DJ, Sanford RN (1950) The authoritarian personality. Harpers and Bros, New York

    Google Scholar 

  • Anderson JR (1996) ACT: a simple theory of complex cognition. Am Psychol 51(4):355–365

    Article  Google Scholar 

  • Asch SE (1955) Opinions and social pressure. Sci Am 193(5):31–35

    Article  Google Scholar 

  • Axelrod R (1973) Schema theory: an information processing model of perception and cognition. Am Polit Sci Rev 67(4):1248–1266

    Article  Google Scholar 

  • Axelrod R (1997) Advancing the art of simulation in the social sciences. Complexity 3(2):16–22

    Article  Google Scholar 

  • Bandura A (1986) Social foundations of thought and action: a social cognitive theory. Prentice Hall, Englewood Cliffs

    Google Scholar 

  • Bandura A, Ross D, Ross SA (1963) Imitation of film-mediated aggressive models. J Abnorm Soc Psychol 66(1):3–11

    Article  Google Scholar 

  • Berger J (2008) Identity-signaling, social influence, and social contagion. In: Prinstein MJ, Dodge KA (eds) Understanding peer influence in children and adolescents. Guilford, New York

    Google Scholar 

  • Bornstein RF (1989) Exposure and affect: overview and metaanalysis of research, 1968–1987. Psychol Bull 106(2):265–289

    Article  Google Scholar 

  • Boyd J (1987) Organic design for command and control. In: A discourse on winning and losing

    Google Scholar 

  • Carley KM (2002) Computational organization science: a new frontier. Proc Natl Acad Sci USA 99(Suppl 3)(90003):7257–7262

    Article  Google Scholar 

  • Centola D (2010) The spread of behavior in an online social network experiment. Science 329(5996):1194–1197

    Article  Google Scholar 

  • Cherry CE (1953) Some experiments on the recognition of speech, with one and with two ears. J Acoust Soc Am 25:975–979

    Article  Google Scholar 

  • Christakis NA, Fowler JH (2008) The collective dynamics of smoking in a large social network. N Engl J Med 358(21):2249–2258

    Article  Google Scholar 

  • Christie R, Geis FL (1970) Studies in machiavellianism. Academic Press, New York

    Google Scholar 

  • Comrey AL (2008) The Comrey personality scales. In: The SAGE handbook of personality theory and assessment: personality measurement and testing. Sage Publications Ltd, Thousand Oaks

    Google Scholar 

  • Dawkins R (1976) The selfish gene. Oxford University Press, New York

    Google Scholar 

  • Edmonds B, Moss S (2005) From KISS to KIDS—an antisimplistic modelling approach. In: Multi-agent and multi-agent-based simulation, pp 130–144

    Chapter  Google Scholar 

  • Fazio RH, Roskos-Ewoldsen DR, Powell MC (1994) Attitudes, perception, and attention. In: Niedenthal PM, Kitayama S (eds) The heart’s eye: emotional influences in perception and attention. Academic Press, New York, pp 197–216

    Chapter  Google Scholar 

  • Fromm E (1973) The anatomy of human destructiveness. Henry Holt, New York

    Google Scholar 

  • Gaver WW (1991) Technology affordances. In: Proceedings of the SIGCHI conference on human factors in computing systems: reaching through technology, pp 79–84

    Google Scholar 

  • Gibson JJ (1979) The ecological approach to perception. Haughton Mifflin, Boston

    Google Scholar 

  • Gibson JJ (1986) The ecological approach to visual perception. Lawrence Erlbaum Associates, Mahwah

    Google Scholar 

  • Haney C, Banks WC, Zimbardo PG (1973a) Interpersonal dynamics in a simulated prison. Int J Criminol Penol 1:69–97

    Google Scholar 

  • Haney C, Banks WC, Zimbardo PG (1973b) Study of prisoners and guards in a simulated prison. Nav Res Rev 9:1–17

    Google Scholar 

  • Hilmert CJ, Kulik JA, Christenfeld NJS (2006) Positive and negative opinion modeling: the influence of another’s similarity and dissimilarity. J Pers Soc Psychol 90(3):440–452

    Article  Google Scholar 

  • Jackson BA (2001) Technology acquisition by terrorist groups: threat assessment informed by lessons from private sector technology adoption. Stud Confl Terror 24(3):183–213

    Article  Google Scholar 

  • James W (1890) The principles of psychology. Harvard University Press, Cambridge

    Book  Google Scholar 

  • Johnston WA, Hawley KJ, Plewe SH, Elliott JMG, DeWitt MJ (1990) Attention capture by novel stimuli. J Exp Psychol Gen 119(4):397–411

    Article  Google Scholar 

  • Kameda T, Ohtsubo Y, Takezawa M (1997) Centrality in sociocognitive networks and social influence: an illustration in a group decision-making context. J Pers Soc Psychol 73(2):296–309

    Article  Google Scholar 

  • Kelley GA (1955) The psychology of personal constructs. WW Norton, New York

    Google Scholar 

  • Laird JE (2008) Extending the soar cognitive architecture. In: Proceedings of the 2008 conference on artificial general intelligence. IOS Press, Amsterdam, pp 224–235

    Google Scholar 

  • Lee DK, Itti L, Koch C, Braun J (1999) Attention activates winner-take-all competition among visual filters. Nat Neurosci 2:375–381

    Article  Google Scholar 

  • Mackintosh NJ (1983) Conditioning and associative learning. Oxford University Press, New York

    Google Scholar 

  • Mantell DM (1971) The potential for violence in Germany. J Soc Issues 27(4):101–112

    Article  Google Scholar 

  • Margolius BH (2001) Permutations with inversions. J Integer Seq 4:01.2.4

    Google Scholar 

  • Michaels CF (2003) Affordances: four points of debate. Ecol Psychol 15(2):135–148

    Article  Google Scholar 

  • Milgram S (2004) Behavioral study of obedience. In: Scheper-Hughes N, Bourgois SP, Bourgois PI (eds) Violence in war and peace. Blackwell Publishers, Boston

    Google Scholar 

  • Nye BD (2011) Modeling memes: a memetic view of affordance learning. Doctoral dissertation, University of Pennsylvania

  • Nye BD, Silverman BG (2012) Affordance(s). In: Seel NM (ed) Encyclopedia of the sciences of learning. Springer, New York

    Google Scholar 

  • O’Brien SP (2010) Crisis early warning and decision support: contemporary approaches and thoughts on future research. Int Stud Rev 12(1):87–104

    Article  Google Scholar 

  • Petty RE, Cacioppo JT (1986) The elaboration likelihood model of persuasion. Adv Exp Soc Psychol 19:123–205

    Article  Google Scholar 

  • Platow MJ, Haslamb SA, Botha A, Chewa I, Cuddona M, Goharpeya N, Maurera J, Rosinia S, Tsekourasa A, Grace DM (2005) “It’s not funny if they’re laughing”: self-categorization, social influence, and responses to canned laughter. J Exp Soc Psychol 41(5):542–550

    Article  Google Scholar 

  • Posner MI, Snyder CR, Davidson BJ (1980) Attention and the detection of signals. J Exp Psychol 109(2):160–174

    Article  Google Scholar 

  • Ray ML, Sawyer AG, Strong EC (1971) Frequency effects revisited. J Advert Res 11(1):14–20

    Google Scholar 

  • Reicher S, Haslam SA (2006) Rethinking the psychology of tyranny: the BBC prison study. Br J Soc Psychol 45(1):1–40

    Article  Google Scholar 

  • Rogers EM (1962) Diffusion of innovations. Free Press, New York

    Google Scholar 

  • Rogers EM (1995) Diffusion of innovations. Free Press, New York

    Google Scholar 

  • Roskos-Ewoldsen DR, Fazio RH (1992) On the orienting value of attitudes: attitude accessibility as a determinant of an object’s attraction of visual attention. J Pers Soc Psychol 63(2):198–211

    Article  Google Scholar 

  • Schreiber C, Carley KM (2007) Agent interactions in construct: an empirical validation using calibrated grounding. In: 2007 conference on behavior representation in modeling and simulation (BRIMS). SISO, Norfolk

    Google Scholar 

  • Shannon CE (1948) A mathematical theory of communication. Key papers in the development of information theory. Retrieved May 2010, from http://cm.bell-labs.com/cm/ms/what/shannonday/shannon1948.pdf

  • Shibuya H, Bundesen C (1988) Visual selection from multielement displays: measuring and modeling effects of exposure duration. J Exp Psychol Hum Percept Perform 14(4):591–600

    Article  Google Scholar 

  • Sikstrom S (1999) Power function forgetting curves as an emergent property of biologically plausible neural network models. Int J Psychol 34(5):460–464

    Article  Google Scholar 

  • Silverman BG (2004) Toward realism in human performance simulation. In: Ness JW, Tepe V, Ritzer DR (eds) The science and simulation of human performance, vol 5. JAI Press, London, pp 469–498

    Chapter  Google Scholar 

  • Silverman BG, Bharathy GK (2005) Modeling the personality & cognition of leaders. In: 2005 conference on behavior representation in modeling and simulation (BRIMS). SISO, Norfolk

    Google Scholar 

  • Silverman BG, Might R, Dubois R, Shin H, Johns M, Weaver R (2001) Toward a human behavior models anthology for synthetic agent development. In: 10th conference on computer generated forces and behavioral representation

    Google Scholar 

  • Silverman BG, Johns M, Cornwell JB, O’Brien K (2006) Human behavior models for agents in simulators and games: part I. enabling science with PMFserv. Presence, Teleoper Virtual Environ 15(2):139–162

    Article  Google Scholar 

  • Silverman BG, Bharathy GK, Nye BD, Eidelson RJ (2007a) Modeling factions for “effects based operations”: part I. Leader and follower behaviors. J Comput Math Organ Theory 13(4):379–406

    Article  Google Scholar 

  • Silverman BG, Bharathy GK, Johns M, Eidelson RJ, Smith TE, Nye BD (2007b) Socio-cultural games for training and analysis. IEEE Trans Syst Man Cybern, Part A, Syst Hum 37(6):1113–1130

    Article  Google Scholar 

  • Silverman BG, Pietrocola D, Nye BD, Weyer N, Osin O, Johnson D, Weaver R (2012) Rich socio-cognitive agents for immersive training environments—case of NonKin Village. Auton Agents Multi-Agent Syst 24(2):312–343

    Article  Google Scholar 

  • Simons DJ, Chabris CF (1999) Gorillas in our midst: sustained inattentional blindness for dynamic events. Perception 28:1059–1074

    Article  Google Scholar 

  • Sun R (2007) Cognitive social simulation incorporating cognitive architectures. IEEE Intell Syst 22(5):33–39

    Article  Google Scholar 

  • Tajfel H (1982) Social psychology of intergroup relations. Annu Rev Psychol 33(1):1–39

    Article  Google Scholar 

  • Tanford S, Penrod S (1984) Social influence model: a formal integration of research on majority and minority influence processes. Psychol Bull 95(2):189–225

    Article  Google Scholar 

  • Tomasello M, Davis-Dasilva M, Camak L, Bard K (1987) Observational learning of tool-use by young chimpanzees. Hum Evol 2(2):175–183

    Article  Google Scholar 

  • Treisman AM, Gelade G (1980) A feature-integration theory of attention. Cogn Psychol 12(1):97–136

    Article  Google Scholar 

  • Vilpponen A, Winter S, Sundqvist S (2006) Electronic word-of-mouth in online environments: exploring referral network structure and adoption behavior. J Interact Advert 6(2):71–86

    Article  Google Scholar 

  • Vygotsky LS (1980) Mind in society. Harvard University Press, Cambridge

    Google Scholar 

  • Wood R, Baxter P, Belpaeme T (2011) A review of long-term memory in natural and synthetic systems. Adapt Behav 20(2):81–103

    Article  Google Scholar 

  • Zentall TR (2007) Imitation: definitions, evidence, and mechanisms. Anim Cogn 9(4):335–353

    Article  Google Scholar 

  • Zimbardo PG (2007) The Lucifer effect: how good people turn evil. Rider, London

    Google Scholar 

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Acknowledgements

Thank you to the Air Force Office of Scientific Research, whose basic research support made this work possible. Also, my sincere thanks to Professor Zimbardo, who was exceptionally responsive and helpful in arranging my access to the archival Stanford Prison Experiment data. Finally, I would like to give a special thanks to the Archives of the History of American Psychology which graciously allowed me to collect data on-site for many days.

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Nye, B.D. Cognitive modeling of socially transmitted affordances: a computational model of behavioral adoption tested against archival data from the Stanford Prison Experiment. Comput Math Organ Theory 20, 302–337 (2014). https://doi.org/10.1007/s10588-013-9162-1

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