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Stream/Area:
-
Subject:
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Paper ID:
IJSREM66953
Volume:
10 |
8 |
Aug 2026
Pages:
1-12
Publication Frequency:
Monthly (12 issues per year)
License:International Journal of Scientific Research in Engineering and Management follows the Creative Commons Attribution 4.0 (CC BY 4.0) License, allowing free use and distribution with proper attribution.
School of Science (BCA)
KK Modi University, Durg
School of Science (BCA)
KK Modi University, Durg
The scientific conceptualization of human personality has transitioned through profound epistemological paradigms, evolving from structuralist introspection to dynamic constructivism, and ultimately into the realm of computational psychometrics. This comprehensive review synthesizes foundational psychological principles, evolutionary adaptive frameworks, and modern artificial intelligence methodologies to elucidate the 16 personality types categorized by the Myers-Briggs Type Indicator (MBTI). The analysis bridges physiological substrates—such as central nervous system architecture and the hypothalamo-pituitary-adrenal axis—with cognitive information processing, behavioral conditioning, and constructivist meaning-making. Furthermore, the report examines personality variance through the lens of evolutionary biology, contrasting human behavioral ecology with gene-culture co-evolution and evolutionary psychology to explain how distinct psychological phenotypes optimize survival and social cohesion. In contemporary contexts, these evolved dispositions interact with digital environments, mediating outcomes related to social capital acquisition, smartphone addiction, and dual-process emotion regulation. Consequently, digital linguistic footprints serve as rich artifacts of latent cognitive architecture. The latter portion of this report critically evaluates the deployment of machine learning algorithms, explicitly comparing traditional probabilistic classifiers with advanced Recurrent Neural Networks equipped with Bidirectional Long Short-Term Memory, to predict MBTI typologies from unstructured social media text. Through this interdisciplinary integration, the report establishes a robust theoretical and empirical foundation for understanding the biological origins, evolutionary utility, and computational predictability of human personality.
KEYWORDS
The conceptualization of human personality has traversed a vast epistemological distance, evolving from the introspective analyses of early structuralists to the sophisticated, hyper-dimensional matrices of modern artificial intelligence. By integrating psychobiology, behavioral conditioning, constructivism, and evolutionary theory, it becomes evident that the 16 personality types mapped by the MBTI represent deeply entrenched evolutionary adaptations and physiological baselines that govern how individuals process information, regulate emotions, and construct their realities. In the modern era, these ancient cognitive architectures are projected into digital ecosystems, leaving behind linguistic artifacts that are highly structured and systematically predictable. The proven efficacy of Recurrent Neural Networks and Bi-LSTM architectures in decoding these textual footprints confirms that human identity is inextricably linked to its linguistic expression. The ongoing synthesis of psychological theory and computational data science promises to continually refine our understanding of the human mind, offering unprecedented tools for therapeutic intervention and organizational optimization while simultaneously demanding rigorous ethical oversight to protect the sanctity of the human psyche.
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Publication Date
8/26/2026
Peer Review Type
Double-Blind Peer Review
Review Rounds: 2
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