Interlinked Narratives: A Comprehensive Review of Network Analysis in the Humanities and Social Science

Abstract

In recent decades, the rise of digital tools and computational methodologies has profoundly influenced the landscape of humanities and social science research. Among these, network analysis has emerged as a powerful approach for understanding complex relationships, patterns, and structures across diverse domains. This paper presents a comprehensive review of how network analysis is applied in the humanities and social sciences, examining both methodological frameworks and real-world applications. It traces the historical development of network thinking, starting from early sociograms and literary linkages to contemporary computational social science and digital humanities projects. In the humanities, network analysis is used to map connections in literary texts, historical correspondence, and cultural interactions, offering new perspectives on authorship, influence, and ideological dissemination. In the social sciences, it enhances our understanding of social capital, power dynamics, and community formation by quantitatively visualizing interpersonal, institutional, and societal networks. The paper also discusses key tools, datasets, and software platforms that facilitate such analyses, including Gephi, Cytoscape, and Pajek, while highlighting the interpretive challenges researchers face in balancing quantitative precision with qualitative depth. Through case studies from literature, history, and digital sociology, this review identifies the main benefits, limitations, and future directions of using network analysis in interdisciplinary research. By integrating data-driven visualizations with contextual interpretation, network analysis not only reveals hidden structures in texts and societies but also transforms traditional academic narratives. This synthesis contributes to a growing body of work that supports a more interconnected and computationally enriched understanding of human culture and social organization.