COMPUTATIONAL
SCIENCE
SOCIAL EXCLUSION AND MENTAL HEALTH: INSIGHTS FROM SIMULATION AND THEORY
Context and Problematic
Social exclusion—both as objective isolation and as the subjective feeling of being left out—has emerged as a key determinant of psychological well-being. Extensive empirical research demonstrates that chronic social disconnection increases risks for depression, anxiety, cognitive decline, and even premature mortality. Yet, distinguishing the independent effects of objective and perceived exclusion remains difficult in observational data, as both often co-occur. Moreover, digital environments now magnify perceived exclusion through constant exposure to curated lives, generating social comparison and “fear of missing out” (FoMO). These modern forms of digital isolation highlight the need for theoretical integration and simulation-based approaches to understand how exclusion dynamics influence mental health over time.
Goal
This study aimed to clarify how real and perceived exclusion each contribute to psychological well-being and physiological stress. By combining computational simulation and theoretical synthesis, it sought to examine the dynamic evolution of mental health and allostatic load under varying degrees of social isolation and loneliness, offering insights consistent with epidemiological and neuropsychological findings.
Method
A simplified simulation of 200 virtual agents was developed, modeling two independent predictors—objective isolation (actual exclusion, AE) and perceived isolation (perceived exclusion, PE)—and one continuous outcome: mental health. Higher MHI (Mental Health Index) values indicated better well-being. The model tested both cross-sectional differences among four isolation–loneliness groups and longitudinal changes over 365 simulated days. Cumulative AE and PE contributions to allostatic load were analyzed to approximate physiological stress accumulation.
Results
Average mental health was high across all groups, though systematically lower under conditions of isolation or loneliness. Agents who were both isolated and lonely had the lowest mean MHI (≈97.5), compared to 99.9 among non-isolated, non-lonely peers. Over time, mean MHI dropped sharply during the first 30 days (~87) and then stabilized near 98.9, suggesting early vulnerability followed by adaptive recovery. Both AE and PE showed additive effects on cumulative allostatic load, with PE exerting a slightly stronger impact, indicating that perceived exclusion may weigh more heavily on stress physiology than objective isolation.
Interpretation
Despite modest numerical differences, the simulation reproduces well-documented human patterns: perceived loneliness and objective isolation independently and cumulatively reduce mental well-being and heighten physiological strain. These findings reinforce the need to address both real and perceived social disconnection—offline and online—to improve mental health and societal resilience.
​
SCHIZO_
COMPUTATIONAL
CAPITALISM
Background
Building on both clinical psychopathology and critical theory, schizocomputational capitalism describes the current digital-economic order that mirrors and produces the fragmentation characteristic of schizophrenia. Classical psychoanalytic conceptions of the “split self” (Freud, Lacan) and Deleuze & Guattari’s notion of “capitalist schizophrenia” provide the groundwork for analyzing how algorithmic capitalism transforms human cognition, affect, and social bonds. Contemporary societies are immersed in computational infrastructures that not only reflect mental disintegration but actively reproduce it through data extraction, emotional manipulation, and symbolic overload.​
Goal
The study aims to conceptualize schizocomputational capitalism as both a metaphor and a systemic condition, demonstrating how algorithmic and affective processes destabilize subjectivity and democratic life. The goal is to show that the political economy of digital capitalism is psychopathogenic: it generates cognitive fragmentation, emotional dysregulation, and social disintegration as inherent outcomes of its operation.​
Method
The analysis combines psychoanalytic theory, political economy, and computational social science. It synthesizes literature from critical media studies, empirical research on algorithmic affect modulation (e.g., Facebook’s emotional-contagion experiment), and sociological data on polarization and misinformation. Three analytical axes are developed: (1) the contradiction economy, which commodifies moral and ideological opposites; (2) affective and algorithmic colonization, which captures and manipulates emotional life; and (3) symbolic overload, which saturates meaning through continuous semiotic noise and simulation.​
Results
The findings reveal a coherent pattern: digital capitalism monetizes dissonance and confusion. Algorithmic systems exploit negativity bias and emotional contagion to sustain engagement, transforming users into fragmented affective feeds. Computational infrastructures blur the distinction between authentic and induced emotion, while hyper-simulated information environments collapse the difference between truth and falsehood. These dynamics collectively erode the “sovereign self” and the shared symbolic frameworks necessary for democratic deliberation.​​
Interpretation and Perspectives
Schizocomputational capitalism thus appears as a pathogenic regime of sense: a system that profits from psychic disorder while undermining collective rationality. Strengthening democratic life will require innovations in regulation, education, and digital architecture—but also recognition that artificial intelligence and corporate power may already outpace human interpretive agency. Whether reform is still possible or a civilizational rupture is inevitable remains an open question. Yet diagnosing these schizoid traits is a necessary first step toward re-imagining a healthier synthesis of technology, psyche, and polis.
​
DIGITAL MOBILITY, SEGREGATION, AND THE UNCONSCIOUS ECONOMIC CODES BEHIND POLARIZATION AND MENTAL DISTRESS
The more we move in digital environments—clicking, swiping, jumping from one group to another—the more we may unknowingly contribute to ideological segregation and social polarization? Unlike the physical world, where mobility was historically limited and coexistence with diverse perspectives was structurally inevitable, digital spaces allow us to escape disagreement in milliseconds. With a single gesture, we leave discomfort and land in echo chambers filled with validation, sameness, and familiar narratives. This hypermobility feels empowering—but it comes at the cost of cognitive plurality and collective dialogue.
​
Computational models like Schelling’s segregation simulations illustrate this dynamic: even when individuals exhibit a high tolerance for diversity, if they are allowed to move freely and widely, they tend to cluster into homogeneous communities. Transposed to digital society, this suggests that the greater our freedom of informational mobility, the more likely we are to seek out the ideologically comfortable. Algorithmic infrastructures further entrench this tendency by amplifying content we already agree with, leading to what researchers describe as “networked homophily”—a feedback loop of identity, preference, and confirmation bias.
​
In this sense, more digital movement doesn’t mean more exposure—it means more self-selected filtering. The result is a paradox: our global information networks were supposed to increase access to plurality, but they often reduce us to narrow islands of shared belief, disconnected from the wider social fabric. Polarization is not a failure of digitality—it’s a logical consequence of its architecture, unless deliberate friction, dialogue, and diversity are reintroduced as core values of digital design.
​
THE EPIGENETIC SCARS OF MODERN LIFE: INTERTWINING STRESS, TECHNOSTRESS, AND HEALTH IN THE CONTEMPORARY WORLD
In today’s hyperconnected world, chronic stress has evolved beyond traditional psychosocial domains to include pervasive digital stressors such as technostress, information overload, and the erosion of work–life boundaries. Advances in epigenetics reveal that persistent stress can leave molecular traces on the genome, influencing health across the lifespan and even transgenerationally. However, the epigenetic effects of digital stressors remain understudied. This review evaluates the biological embedding of psychosocial and digital stress, focusing on DNA methylation, histone modification, and telomere attrition as potential mechanisms. Drawing on over 150 interdisciplinary sources, it synthesizes findings from neuroscience, psychology, and molecular biology to assess how stress pathways—especially involving the HPA axis, inflammation, and sympathetic activation—may mediate the impact of technostress. Particular attention is given to vulnerable populations such as older workers, remote employees, and youth, as well as protective factors like mindfulness and health-oriented leadership.
​
Evidence confirms that technostress is consistently linked to burnout, anxiety, and depression, while physiological data suggest dysregulation of the HPA axis and elevated inflammatory markers. Though epigenetic data specific to digital stress are still emerging, studies on sleep disruption, cognitive overload, and work strain point to plausible mechanisms of epigenetic impact. Research from the PROAGEING study and other cohorts suggests associations between technostress and biological aging markers such as telomere shortening and altered methylation in stress-sensitive genes (e.g., NR3C1, BDNF). These findings support the idea that technostress is a biologically active environmental stressor capable of reshaping health trajectories. This shift calls for public health and occupational medicine to recognize digital exposures as legitimate contributors to stress-related illness and to expand epigenetic research to systematically include digital lifestyle variables.
​
UNCONSCIOUS ECONOMIC CODES AND MENTAL HEALTH DISORDERS: A TWO-LEVEL THEORETICAL MODEL
This exploration proposes a dual-level model articulating the dissemination of unconscious economic codes through social institutions and their internalization by individuals, contributing to the development of mental distress and psychiatric disorders. Drawing on clinical psychology, computational sociology, and critical theory, we argue that economic logic—embedded in cultural environments—is unconsciously transmitted, internalized, and reproduced in daily life. The model links systemic and individual factors, offering insights for both simulation-based research and public health policy.
​
​
THE ILLUSION AS METHOD AND IDEOLOGY: COMPUTATIONAL SOCIOLOGY, VISION AND SIMULATION
In an era defined by algorithmic governance, digital spectacle, and perceptual overload, classical sociological methods prove insufficient to grasp the complexity of contemporary social life. This work explores the convergence of computational sociology, social simulation, and vision as a new epistemological paradigm—one in which perception, simulation, and emergent behavior are not only studied but mobilized as tools to model and shape the social world. Drawing from agent-based modeling, computational vision, and critical theory, the study demonstrates how simulation is no longer a condition of postmodern illusion but a methodological engine for generating and governing social realities. Through case studies such as Cambridge Analytica and phenomena like astroturfing, nudging, and algorithmic vision, we show how interpretive frames and visual regimes are embedded into simulations to test and steer behavior, often reinforcing symbolic hierarchies and political agendas. By modeling how agents perceive and act upon visual and affective stimuli, we uncover how perception itself becomes a site of power. The implications for mental health, democratic coherence, and social inequality are profound. This fusion of disciplines invites a critical rethinking of sociology—not as a mirror of reality, but as a laboratory for anticipating systemic collapse and designing new perceptual and political infrastructures.
​