Abstract

This paper explores the intersection of digital humanities and hermeneutics, proposing a model that differentiates between soft and hard Digital Hermeneutics. Soft hermeneutics refers to human-centered interpretation processes, while hard hermeneutics focuses on machine-driven data processing. The paper argues that both forms of interpretation are complementary and necessary to fully understand and navigate complex digital datasets. Through three case studies—in clinical hermeneutics, political opinion analysis, and digital library configuration—the work illustrates how Natural Language Processing (NLP) techniques, combined with human interpretative methods, contribute to emerging practices in the field. By blending traditional humanities approaches with computational methods, the paper highlights the creation of a new hermeneutic paradigm that integrates qualitative and quantitative strategies. This paradigm underscores the vital role of human interpretation in complementing automated analysis within digital humanities. Finally, the paper reflects on how Digital Hermeneutics reframes the relationship between human agency and technology in interpreting data-driven content.