A Conceptual Approach to Bridging the Relationship Between Computational Intelligence & The Social Sciences: An Applied Computational Model
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https://orcid.org/0000-0002-8089-2066
Abstract
Text Network Analysis (TNA) serves as a potent tool for dissecting various forms of textual e-content, offering profound insights into their underlying structures. In this study, we illuminate the potential of harnessing computational intelligence within the realm of social sciences by applying Text Network Analysis to a seminal work in the sociology of knowledge. Authored by two scholars, this work delves into the intricate interplay between reality, society, and knowledge.
Our utilization of computational intelligence tools has proven adept at discerning the epistemic phrases and concepts embedded within the text, unraveling the intricate tapestry of the authors' discourse and revealing a rich tapestry of social and epistemic concepts. The computational approach yielded a reading coefficient of 16.943, indicative of the material's challenging nature. Furthermore, an analysis of the book's content highlighted the prominence of key terms: Reality, Knowledge, Social, Society, and World. To augment our understanding, we visually represented the connections between the book's vocabulary and the meanings inherent in its text. We then delved deeper into the network fabric of three conceptual domains: Social-Reality-Knowledge, Social-Society, and World-Society-Individual. The analysis unveiled the intricate relationships within these concept networks, offering invaluable insights for social science students and researchers, streamlining analysis processes, and saving valuable time. This innovative approach to computationally processing social texts serves as a bridge between the realms of smart computing and social sciences, paving the way for new synergies and expanded horizons at the intersection of these two fields of knowledge.
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Social SciencesComputational IntelligenceText Network AnalysisText VisualizationConcept Networks
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