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- W2185369078 abstract "In this research we propose a method for visualizing text’s polysingularity: the multiple clusters of meaning circulation contained within a text. These clusters can be described as “strange attractors” (to use the term from dynamical systems theory), which are actualized during the process of reading. We use network analysis in order to plot the text’s structure onto a two-dimensional plane and represent these strange attractors as the communities of co-occurring nodes, positioned within the graph depending on their influence for the production of meaning. Such visual representation can then be used to identify the most influential topics within the text, provide quick summaries, enhance text comprehension (aiding the retainment of previous information according to the Landscape model of reading), create interfaces for inter-textual navigation, produce individual or group “mental maps”, and perform comparative analysis of texts. Our method can also improve the existing graphical methods for identifying topical structure (pLSA and DLA) in that it takes into account the overall structure of text for analysis and also brings in the tools and approaches used in network and graph analysis to further enhance qualitative and quantitive evaluation of textual data." @default.
- W2185369078 created "2016-06-24" @default.
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- W2185369078 date "2012-01-01" @default.
- W2185369078 modified "2023-09-23" @default.
- W2185369078 title "Visualization of Text's Polysingularity Using Network Analysis" @default.
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