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In our paper we would like to make a cross-disciplinary leap and use thetools of network theory to understand and explore narrative structure inliterary fiction, an approach that is still underestimated. However, thesystems in fiction are sensitive to readers subjectivity and attention must tobe paid to different methods of extracting networks. The project aims atinvestigating into different ways social interactions are read in texts bycomparing networks produced by automated algorithms-natural language processingwith those created by surveying more subjective human responses. Conversationnetworks from fiction have been already extracted by scientists, but the moregeneral framework surrounding these interactions was missing. We proposeseveral NLP methods for detecting interactions and test them against a range ofhuman perceptions. In doing so, we have pointed to some limitations of usingnetwork analysis to test literary theory, e.g. interaction, which correspondsto the plot, does not form climax.

Social Networks Analysis in Discovering the Narrative Structure of Literary Fiction