Digital environments have transformed the speed, scale, and volatility of social identity and norm shifts. Classic frameworks—such as Social Identity Theory, Self-Categorization Theory, and Norm Focus Theory—describe identity dynamics but cannot fully account for rapid polarization, sudden identity leaps, and large-scale normative realignments emerging on social media. This article proposes Networked Identity-Calibration Theory (NICT), a comprehensive multi-level theory integrating identity salience, normative calibration, emotional amplification, and network topology. NICT posits that identity states evolve through a dynamic calibration process in which individuals adjust their identity position based on weighted normative signals from network peers, and these signals are strongly intensified by emotional content and network structure. When cumulative signals surpass an individual’s identity threshold, a rapid transition—an identity leap—occurs, pushing the person into a new identity equilibrium. The theory identifies mechanisms, boundary conditions, and testable propositions, supported by a preliminary mathematical model that formalizes calibration, emotional weighting, and threshold dynamics. NICT contributes a unified account of how identity becomes polarized, how toxic norms emerge, and how algorithmically shaped networks accelerate identity change. It provides practical implications for platform design, public policy, and interventions aimed at enhancing identity resilience and mitigating polarization. Keywords: social identity; norm calibration; emotional amplification; digital networks; polarization; identity leap; social media; computational social psychology; network topology; collective behavior