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Computational and Data-Driven Gellnerian Social Theory: From the Transition to Modernity to a Disenchanted Future

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Computational and data-driven approaches in social science have become increasingly popular in recent years, in tandem with the rise of artificial intelligence. Gellner’s social theory may seem far removed from these approaches, but in fact the clarity of his analytical and comparative-historical account of social change lends itself to formalization and data-driven testing, thus allowing evaluation in relation to rival social theories. Gellner’s social thought also embraced empiricism and mechanism, which aid causal explanations and so contribute to cumulative social scientific knowledge. This chapter examines Gellner’s social theory with a view to how it fares when put to the test of recent computational social science approaches, which include visualizing causal pathways. A starting point here is Gellner’s conception of the transition to modernity, which has been much discussed, where he aims to pinpoint the main explanations. And one example of how his thought can inform analysis of the future of modernity is climate change, where current trends will, without major course corrections, inexorably lead to greater coercion. Gellner did not anticipate data-driven computational approaches, but his thought provides important guideposts for cumulation in keeping with this new turn in the social sciences.KeywordsGellnerSocial theoryComputational social scienceModernityClimate change

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