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Introduction

People differ on stable psychological traits, e.g. the Big Five framework is the dominant operationalisation, and these traits predict everything from career choices to political participation to health outcomes. Until recently, personality research has been constrained by self-report questionnaires that cannot scale beyond a few thousand participants. The advent of digital traces (social-media text, mobility data, visual content, smartphone sensors) and AI-based inference methods has shifted the constraint: we can now estimate personality at the scale of millions and aggregate the estimates to regional units (counties, cities, nations).

My current work introduces a Domain–Scope Framework for AI-based personality inference, maps the methodological landscape across linguistic, visual, audio, smartphone, physiological and multimodal data sources, and applies the resulting infrastructure to substantive questions: how regional personality shapes entrepreneurship, residential mobility, urban resilience, and voting. A meta-analysis of geographic personality research across 36 published studies and a methodological review of 95 papers in AI-based personality inference provide the empirical and analytical backbone.

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