Modeling narrative structure and dynamics with networks, sentiment analysis, and topic modeling


Autoři: Semi Min aff001;  Juyong Park aff001
Působiště autorů: Graduate School of Culture Technology, Korea Advanced Institute of Science & Technology, Daejeon, Republic of Korea aff001;  BK21 Plus Postgraduate Program for Content Science, Daejeon, Republic of Korea aff002;  Sainsbury Laboratory, University of Cambridge, Cambridge, United Kingdom aff003
Vyšlo v časopise: PLoS ONE 14(12)
Kategorie: Research Article
prolekare.web.journal.doi_sk: 10.1371/journal.pone.0226025

Souhrn

Human communication is invariably executed in the form of a narrative, an account of connected events comprising characters, actions, and settings. A coherent and well-structured narrative is therefore essential for effective communication, confusion caused by a haphazard attempt at storytelling being a common experience. This also suggests that a scientific understanding of how a narrative is formed and delivered is key to understanding human communication and dialog. Here we show that the definition of a narrative lends itself naturally to network-based modeling and analysis, and they can be further enriched by incorporating various text analysis methods from computational linguistics. We model the temporally unfolding nature of narrative as a dynamical growing network of nodes and edges representing characters and interactions, which allows us to characterize the story progression using the network growth pattern. We also introduce the concept of an interaction map between characters based on associated sentiments and topics identified from the text that characterize their relationships explicitly. We demonstrate the methods via application to Victor Hugo’s Les Misérables. Going beyond simple, aggregate occurrence-based methods for narrative representation and analysis, our proposed methods show promise in uncovering its essential nature of a highly complex, dynamic system that reflects the rich structure of human interaction and communication.

Klíčová slova:

Built structures – Community structure – Complex systems – Computational linguistics – Culture – Emotions – Language – Network analysis


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2019 Číslo 12