This manuscript proposes a sequential framework for computational hermeneutics that connects historical textual archives, large-scale computational analysis, contextual interpretation, and institutional foresight within a single interpretive pipeline. The framework begins with textual archive ingestion and distant reading, where corpora are transformed into signal-bearing fields through n-gram analysis, topic modeling, collocation mapping, and publication dynamics. It then advances to contextualization and synthesis, where computational pattern detection is reconnected to close reading, semantic nuance, and historical explanation. A third stage introduces an analytical mediation layer that links macroscopic data structures to microscopic interpretive units through filters, Keywords-in-context analysis, semantic prosody, and morphing relational structures. The fourth stage tracks epistemic shift topology, emphasizing conceptual drift, traceability, source anchoring, and the movement of terms across semantic and institutional environments. The final stage models institutional crystallization and foresight, showing how discursive shifts become legible as adoption signals, technological materialization, and organizational change. Taken together, the framework repositions computational hermeneutics not merely as a toolkit for distant reading, but as a cyclical methodology for moving from textual history to interpretive explanation and, ultimately, to strategic institutional analysis. The result is a manuscript architecture that integrates cultural signal detection, semantic interpretation, and institutional evolution into one coherent sequence.
Umair Abbas (Thu,) studied this question.