DIGITAL MOBILITY, SEGREGATION, AND THE UNCONSCIOUS ECONOMIC CODES BEHIND POLARIZATION AND MENTAL DISTRESS

In our increasingly digitized world, the paradox of movement and isolation is no longer limited to the physical realm. The freedom to traverse digital landscapes—social media platforms, virtual communities, educational forums, and algorithmically curated environments—appears to promise openness, diversity, and multiplicity. Yet, as computational simulations such as Schelling’s segregation model and its contemporary extensions suggest, this very mobility might accelerate processes of polarization and social fragmentation. In contrast to early internet utopias of collective intelligence and multicultural dialogue, we now witness the entrenchment of ideological bubbles, the marginalization of dissenting voices, and the erosion of shared cognitive environments.

 

A key insight drawn from agent-based modeling and artificial societies is that expanding one’s “circle of influence” (i.e., the number of individuals whose behaviors and attributes affect a given agent’s decisions) paradoxically leads not to diversity but to intensified conformity and segregation. In one simulation using a 48-cell neighborhood within an assimilation setup, agents increasingly adapted to the majority, leaving minority opinions and affiliations to vanish or cluster in isolated zones. This dynamic mirrors digital reality: the more we are exposed to algorithmic amplification and personalized content flows, the more likely we are to seek confirmation rather than contradiction, belonging rather than tension. This phenomenon of digital self-sorting is not merely a social trend—it has become a structuring principle of modern life, deeply embedded in how we educate, communicate, and interpret the world.

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But these emergent behaviors cannot be understood merely as matters of individual preference or cognitive bias. What remains profoundly underexplored in mainstream computational modeling is the role of unconscious economic codes—invisible, internalized imperatives that silently govern behavior in digital systems. These codes do not emerge ex nihilo; they are injected through design choices, platform incentives, educational protocols, and socio-cultural conditioning. For instance, the commodification of attention (Zuboff, 2019), the gamification of communication (Han, 2017), and the optimization of performance metrics (Berardi, 2009) operate not only at the interface level but seep into the very psychological fabric of users. Underneath the conscious engagement with content lies a deeper alignment with economic logic—productivity, efficiency, visibility, and competition—that defines social interactions and mental representations.

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This is particularly evident in the way digital practices are entangled with educational and social environments. Schools and online learning platforms often promote standardization, assessment-oriented thinking, and competition as implicit values, embedding capitalist productivity codes into pedagogical design (Williamson, 2017). In parallel, platforms like LinkedIn, Twitter (now X), and even TikTok implicitly valorize social success, personal branding, and performative activism. These norms shape what users post, how they interact, and even what they believe. Such structuring codes are not merely social but economic—they link individual worth to visibility, consistency to engagement, and divergence to failure.

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Within this framework, mental health is no longer simply a question of subjective well-being or neurochemical balance. The exposure to algorithmic segregation and economic normativity places individuals in a state of economic and affective overcoding, where constant comparison, performativity, and isolation undermine psychic equilibrium. As the digital subject increasingly inhabits a world where the like-minded is always only one click away, a compulsion emerges to escape dissonance and seek hyper-alignment. The result is not greater satisfaction, but chronic anxiety, fear of exclusion, and a permanent state of self-surveillance. These psychosocial dynamics—while appearing personal—are in fact symptoms of a broader socio-economic apparatus that rewards alignment and punishes ambiguity.

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Simulation models thus offer more than empirical illustrations of segregation. They are epistemological tools to explore how micro-motives—when shaped by macro-structures—produce emergent patterns that are qualitatively distinct from individual intentions. Schelling’s original model showed that even relatively tolerant agents could, through local decisions, create highly segregated environments. The same logic applies to digital behavior: users seeking simply to engage or be understood often contribute to collective phenomena of polarization and fragmentation.

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To address these complexe challenges, critical digital theory must incorporate insights from computational sociology, psychology, and economic semiotics. We must interrogate not only the visible behaviors of agents, but the hidden codes—social, cultural, and economic—that configure these behaviors beneath the level of awareness. These codes must be studied in their intersubjective manifestations: in how users interact, conform, avoid, or compete within seemingly “free” digital systems. Mental health research must take seriously the economic unconscious, not as a metaphor but as a structural force that shapes identity, cognition, and interpersonal dynamics.

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Recent studies have linked digital hyper-connectivity to rising levels of anxiety, depression, and social withdrawal among adolescents and young adults (Twenge et al., 2017; Orben & Przybylski, 2019). However, these analyses often remain descriptive, failing to account for how economic codes—like the imperative to be constantly “on,” visible, and optimized—mediate these symptoms. A critical economic-psychological approach would instead investigate how mental illness today is, in many cases, a rational response to irrational socio-economic demands: to the impossible ideals of constant connectivity, perpetual productivity, and frictionless self-expression.

 

The idea of digital mobility as a vehicle for empowerment must be problematized. As the simulations demonstrate, high mobility enables agents to find like-minded others and escape discomfort—but at the price of increasing homogeneity and reducing social complexity. The disappearance of shared spaces, friction, and contradiction undermines the very conditions for democratic discourse and pluralism. In a world where one can instantly exit discomfort, there is little incentive to negotiate difference or tolerate ambiguity. Thus, the digital public sphere becomes a set of parallel monologues, each enclosed within its own bubble of economic and ideological coherence.

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This condition has significant consequences for collective intelligence and epistemic health. When exposure is governed by personalization and driven by underlying economic incentives (clicks, conversions, time spent), the result is not serendipity but selective amplification. Minority voices, unconventional perspectives, and unmarketable knowledge are algorithmically marginalized. The result is not only informational inequality but cognitive monoculture—a state of collective myopia enforced not by authoritarian censorship, but by unconscious economic structuration.

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Confronting this requires a shift in both research and intervention. Social simulations must integrate economic semiotics into their models—examining not just agents and preferences, but how those preferences are shaped by platform logics, educational trajectories, and economic aspirations. Mental health practitioners must include in their frameworks the impact of digital labor, algorithmic exposure, and normative pressures on psychic life. And educational reform must resist the metrics-driven alignment with market logic, promoting instead dialogic, pluralistic, and critical pedagogies.

 

Digital mobility has created new landscapes of belonging, but it has also enabled new forms of exclusion, segregation, and psychic burden. These patterns are not accidental—they are the predictable consequences of a system that encodes economic imperatives into every click, scroll, and post. Recognizing the economic unconscious behind digital polarization is the first step toward imagining alternative models—of connection, of thought, and of society.

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REFERENCES

Berardi, F. (2009). The Soul at Work: From Alienation to Autonomy. Semiotext(e).

Han, B.-C. (2017). Psychopolitics: Neoliberalism and New Technologies of Power. Verso Books.

Orben, A., & Przybylski, A. K. (2019). The association between adolescent well-being and digital technology use. Nature Human Behaviour, 3(2), 173–182.

Schelling, T. C. (1978). Micromotives and Macrobehavior. W. W. Norton & Company.

Twenge, J. M., Joiner, T. E., Rogers, M. L., & Martin, G. N. (2017). Increases in depressive symptoms, suicide-related outcomes, and suicide rates among U.S. adolescents after 2010 and links to increased new media screen time. Clinical Psychological Science, 6(1), 3–17.

Williamson, B. (2017). Big Data in Education: The Digital Future of Learning, Policy and Practice. SAGE.

Zuboff, S. (2019). The Age of Surveillance Capitalism. PublicAffairs.

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