Cognitive biases in cyber fraud practices: the heuristic potential of M. Norton's theory
Research Article
Acknowledgments
The reported study was funded by the Russian Science Foundation grant no. 23–28–00701, “Behavioral strategies of consumers of financial services in the context of cyberfraud: an interdisciplinary analysis”
How to Cite
Vasilkova V.V. (2024) Cognitive biases in cyber fraud practices: the heuristic potential of M. Norton’s theory. Zhurnal sotsiologii i sotsialnoy antropologii (The Journal of Sociology and Social Anthropology), 27(4): 202–237 (in Russian). DOI: https://doi.org/10.31119/jssa.2024.27.4.7 EDN: LEQQSA
Abstract
The concept of cognitive biases, introduced in 1972 by D. Kahneman and A. Tversky and identifying the cause of erroneous decisions in human economic behavior, has become one of the explanatory models in describing the practices of modern cyber fraud. However, the growing scale and negative consequences of cyber fraud actualize the need to expand the interpretations of this phenomenon in the context of various disciplines, primarily sociology, which allows us to overcome the narrowly individual approach that links cognitive distortions only with the mental characteristics of human thinking and to set the vector of analysis of their socio-cultural determination. The article examines the heuristic prospects of using the concepts of cognitive sociology (in particular, M. Norton’s theory) as an interpretative model for the analysis of cognitive distortions in cyber fraud practices. This approach allows us to give a broad interpretation of this phenomenon as a necessary attribute of the general process of socio-cultural semiosis, to explain the manipulative nature of specific semiotic contours that determine the choice of a certain type of human action and the activation of specific cognitive distortions, to understand how certain cognitive distortions influence such a choice in a situation of cyber fraud, to show the conjugation of cognitive mechanisms and the socio-cultural environment in the process of forming networks of meanings in the “semiosis of cyber fraud”. The theoretical provisions of Norton's concept are examined using specific examples of such cognitive distortions as the authority effect, the trust effect, and the confirmation bias.
Keywords:
cognitive biases, cyber fraud, cognitive sociology, semiosis, authority bias, trust effect, confirmation bias
References
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Канеман Д. (2016) Думай медленно… решай быстро. М.: АСТ.
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Кашапова Э.Р., Рыжкова М.В. (2015) Когнитивные искажения и их влияние на поведение индивида. Вестник Томского государственного университета. Экономика, 2(30): 15–26.
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Корниенко А.А. (2013) Эволюция парадигмы когнитивной социологии науки в западной философии науки. Вестник Томского государственного университета. Культурология и искусствоведение, 3(11):74–79.
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Kurakin D. (2018) Preface to the Russian translation of “Elementary Forms of Religious Life”. In: Durkheim E. Elementary Forms of Religious Life: The Totemic System in Australia. Moscow: Elementary Forms: 15–48 (in Russian).
Медяник О.В. (2023) Исследование когнитивных искажений в цифровой экономике и праве. Юридическая мысль, 3(131): 33–71.
Medyanik O.V. (2023) Research of cognitive distortions in digital economy and law. Yuridicheskaya mysl’ [Legal thought], 3(131): 33–71 (in Russian).
Михайлов И.Ф. (2021) Когнитивные основания социальности: Дис. … д-р филос. н. Москва.
Mikhaylov I.F. (2021) Cognitive foundations of sociality. Dissert na soisk. uchenoy. stepen. d.filos.n. [Dissertation for the degree of Doctor of Philosophy]. Moscow (in Russian).
Плотинский Ю.М. (2001) Модели социальных процессов. 2-е изд. М.: Логос.
Plotinskiy Y.M. (2001) Models of social processes. 2ed. Moscow: Logos (in Russian).
Попов Ю.А., Вихман А.А. (2014) Когнитивные искажения в процессе принятия решений: научная проблема и гуманитарная технология. Вестник ЮУрГУ. Сер. Психология, 7(1): 5–16.
Popov Y.A., Vikhman A.A. Cognitive distortions in the decision-making process: a scientific problem and humanitarian technology. Vestnik YUUrGU. Seriya Psikhologiya [Bulletin of SUSU. Series Psychology], 7(1): 5–16 (in Russian).
Тобышева А.А., Шубат О.М. (2023) Теоретические подходы к анализу когнитивных искажений как фактора корпоративной демографической политики. Демографические факторы адаптации населения к глобальным социально-экономическим вызовам. Екатеринбург: 722–732.
Tobysheva A.A., Shubat O.M. (2023) Theoretical approaches to the analysis of cognitive distortions as a factor in corporate demographic policy. In: Demographic factors of population adaptation to global socio-economic challenges. Ekaterinburg: 722–732 (in Russian).
Шариков Д.Д. (2019) Новая социология культуры: от «ящиков с инструментами» к когнитивным процессам. Журнал социологии и социальной антропологии, 22(3): 179–210. https://doi.org/10.31119/jssa.
Sharikov D. (2019) The new sociology of culture: from toolkits to cognitive processes. Zhurnal sotsiologii i sotsialnoy antropologii [The Journal of Sociology and Social Anthropology], 22(3): 179–210. https://doi.org/10.31119/jssa.2019.22.3.8 (in Russian).
Beattie P., Beattie M. (2023) Political polarization: a curse of knowledge? Frontiers in psychology, 14: 1200627. https://doi.org/10.3389/fpsyg.2023.1200627.
Bazerman M. (2005) Judgment in Managerial Decision Making. Hoboken, NJ: John Wiley & Sons.
Bellé N., Cantarell P., Belardinelli P. (2018) Prospect theory goes public: experimental evidence on cognitive biases in public policy and management decisions. Public Administration Review, 78: 828–840. https://doi.org/10.1111/puar.12960.
Borwell J., Jansen J., Stol W. (2021) Comparing the victimization impact of cybercrime and traditional crime: Literature review and future research directions. Journal of Digital Social Research, 3(3): 85–110. https://doi.org/10.33621/jdsr.v3i3.66.
Cicourel A.V. (1973) Cognitive Sociology. London: Pinguin Education.
DiMaggio P. (1997) Culture and cognition. Annual sociological review, 23: 263–287.
French A., Storey V., Wallace L. (2023) The impact of cognitive biases on the believability of fake news. European Journal of Information Systems, 1 Nov. https://doi.org/10.1080/0960085X.2023.2272608.
Hansen K., Gerbasi M., Todorov A., Kruse E., Pronin E. (2014) People claim objectivity after knowingly using biased strategies. Personality and Social Psychology Bulletin, 40: 691–699. https://doi.org/10.1177/0146167214523476.
Haselton M.G., Nettle D., Andrews P.W. (2005) The evolution of cognitive bias. In: Buss D.M. (ed.). The Handbook of Evolutionary Psychology. Hoboken, NJ: John Wiley & Sons Inc.: 724–746.
Hilbert M. (2012) Toward a synthesis of cognitive biases: how noisy information processing can bias human decision making. Psychological Bulletin, 138 (2): 211–37. https://doi.org/10.1037/a0025940. PMID 22122235.
Kahneman D., Tversky A. (1972) Subjective probability: A judgment of representativeness. Cognitive Psychology, 3(3):430–454. https://doi.org/10.1016/0010–0285(72)90016-3.
Kahneman D., Slovic P., Tversky, A. (eds.) (1982) Judgment Under Uncertainty: Heuristics and Biases. New York: Cambridge University Press.
Kahneman D., Tversky A. (1984). Choices, values, and frames. American Psychologist, 39(4): 341–350. https://doi.org/10.1037/0003–066X.39.4.341.
Kaidesoja T., Hyyryläinen М., Puustinen R. (2022) Two traditions of cognitive sociology: An analysis and assessment of their cognitive and methodological assumptions. Journal for the Theory of Social Behaviour, 52: 528–547. https://doi.org/10.1111/jtsb.12341.
Korteling J. E., Gerritsma J., Toet A. (2021). Retention and transfer of cognitive bias mitigation interventions: a systematic literature study. Frontiers in psychology, 12: 629354. https://doi.org/10.3389/fpsyg.2021.629354, PMID.
Korteling J.E., Paradies G.L., Sassen-van Meer J.P. (2023) Cognitive bias and how to improve sustainable decision making. Frontiers in psychology, 14: 1129835. https://doi.org/10.3389/fpsyg.2023.1129835.
Korteling J. E., Toet A. (2022) Cognitive biases. In: Della Sala S. (ed.) Encyclopedia of Behavioural Neuroscience. 2nd ed.: 610–619.
Kostopoulou O., Porat T., Corrigan D., Mahmoud S., Delaney B. C. (2017) Diagnostic accuracy of GPs when using an early-intervention decision support system: a high-fidelity simulation. The British journal of general practice, 67 (656), e201–e208. https://doi.org/10.3399/bjgp16X688417.
Lizardo O. (2017) Improving cultural analysis: Considering personal culture in its declarative and nondeclarative modes. American Sociological Review, 82(1): 88–115. https://doi.org/10.1177/0003122416675175.
Ludolph R., Schulz P. J. (2018) Debiasing health-related judgments and decision making: a systematic review. Medica decision making, 38(3): 3–13. https://doi.org/10.1177/0272989X17716672.
MacCoun R.J. (1998) Biases in the interpretation and use of research results. Annual Review of Psychology, 49 (1): 259–287. https://doi.org/10.1146/annurev.psych.49.1.259. PMID 15012470.
McGee R.J., Warms R.L. (eds.) (2008) Anthropological theory: an introductory history. 4th ed. New York: McGraw-Hill Education.
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Article
Received: 29.07.2024
Accepted: 25.12.2024
Citation Formats
Other cite formats:
ACM
[1]
Vasilkova, V.V. 2024. Cognitive biases in cyber fraud practices: the heuristic potential of M. Norton’s theory. Zhurnal sotsiologii i sotsialnoy antropologii (The Journal of Sociology and Social Anthropology). 27, 4 (Dec. 2024), 202–237. DOI:https://doi.org/10.31119/jssa.2024.27.4.7.
Section
Cognitive Sociology
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