<![CDATA[The digital transformation of contemporary society has reshaped religious authority, identity construction, and intra-religious interaction. Social media platforms now function as primary arenas for theological negotiation, organizational affiliation, and discursive contestation within religious communities. In this context, intra-religious tolerance—the capacity to accept doctrinal, interpretive, and organizational diversity within the same religious tradition—has become increasingly mediated by algorithmic systems and digitally structured communication environments. Traditional survey-based and ethnographic approaches face limitations in capturing large-scale, real-time patterns of tolerance and polarization. This study develops a comprehensive conceptual framework for measuring intra-religious tolerance through a computational social science approach grounded in big data analytics. Using a qualitative research design based on systematic literature review (2016–2025), thematic synthesis, and conceptual integration, the study bridges scholarship in computational social science, big data methodologies, sociology of religion, and social psychology. The findings propose a multidimensional tolerance model encompassing cognitive, affective, behavioral, and algorithmic-structural dimensions. The article introduces a Big Data-Based Intra-Religious Tolerance Index (IRIT Index) grounded in digital trace indicators such as sentiment polarity, interaction diversity, network modularity, and hostility frequency. The framework contributes theoretically by integrating macro-sociological and micro-psychological theories within computational measurement paradigms, and methodologically by advancing qualitative conceptual modeling within data-intensive research. Ethical considerations, epistemological challenges, and implications for digital governance are discussed.]]>
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