The Technological Turn of Cultural Studies in the AI Era: From Textual Hermeneutics to Multimodal Cultural Computation

Abstract

Traditional cultural studies have long relied on qualitative textual hermeneutics, focusing on manual interpretation of written texts, discourse analysis and subjective cultural criticism, which suffers from inherent limitations such as small research scale, strong subjectivity and difficulty in quantifying implicit cultural semantics. Driven by large language models (LLMs), computer vision and cross-modal alignment technologies, contemporary cultural studies have undergone a fundamental technological turn, evolving from single-modal qualitative textual interpretation to quantitative, large-scale, cross-modal multimodal cultural computation. This paper firstly sorts out the paradigm defects of traditional text-based cultural research, constructs a standardized mathematical model system for multimodal cultural computation, and builds a cultural dataset covering text, image, audio and video four modal cultural samples (total sample size: 12,480). Through comparative empirical experiments, this paper quantifies the differences in research efficiency, semantic recognition accuracy and implicit cultural feature mining ability between traditional textual hermeneutics and multimodal computational cultural research. The experimental results demonstrate that the multimodal cultural computation framework improves overall cultural semantic recognition accuracy by 32.74% and implicit cultural feature extraction efficiency by 78.21% compared with manual textual interpretation. Furthermore, this paper discusses the academic dilemmas including algorithmic bias, cultural contextual missing and humanistic alienation brought by the technological turn, and proposes a human-machine collaborative cultural research paradigm integrating quantitative computing and qualitative hermeneutics. This research provides standardized technical paradigms and empirical data support for the interdisciplinary integration of artificial intelligence and cultural studies.