Social Network Analysis in Literary Contexts
Summary
Social network analysis in literary contexts employs graph‐theoretical methods to map and quantify relationships among characters, settings and events within narrative texts. By representing characters as nodes and their interactions as edges, researchers reveal underlying structures that shape plot development, thematic coherence and reader engagement. Metrics such as degree distributions, centrality measures and community detection uncover patterns of influence, alliance and conflict, offering fresh insights into authorial design and cultural resonance. Dynamic approaches trace the evolution of networks through successive chapters or episodes, highlighting turning points and the interplay of subplots. When coupled with sentiment analysis and topic modelling, social network frameworks enrich our understanding of emotional trajectories and thematic clusters. Globally, this interdisciplinary field bridges digital humanities, computational linguistics and complexity science, with applications ranging from literary pedagogy and heritage preservation to the development of AI‐assisted storytelling and interactive media.
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Social Network Analysis in Literary Contexts publication trend
The graph below shows the total number of articles in social network analysis in literary contexts across all publications each year (not limited to Nature Index journals).
Technical terms
Social network analysis: systematic study of relationships among entities using graph theory to model and analyse connections.
Node: an individual entity within a network, such as a character or location in a narrative.
Edge: a link representing an interaction, dialogue or relationship between two nodes.
Centrality: a measure of a node’s prominence or influence within a network, indicating its relative importance.
Community detection: computational methods that identify clusters of nodes with dense internal connections, revealing subgroups or narrative threads.
References
- Narrative structure of A Song of Ice and Fire creates a fictional world with realistic measures of social complexity. Proceedings of the National Academy of Sciences of the United States of America (2020).
- Modeling narrative structure and dynamics with networks, sentiment analysis, and topic modeling. PLOS ONE (2019).
- Network analysis of the Viking Age in Ireland as portrayed in Cogadh Gaedhel re Gallaibh. Royal Society Open Science (2018).
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