• Textexture: The Non-Linear Reading Machine

    When we read a text, we normally follow it in quite a linear fashion: from left to right, from top to bottom. Even when we skim articles quickly online, the trajectory is still the same. However, this is not the most efficient method of reading: in the age of hypertext we tend to create our own narratives using the bits and pieces from different sources. This is an easy task with short Tweets or Facebook posts, but it becomes much more difficult when we’re dealing with newspaper articles, books, scientific papers. The amount of information we’re exposed to increases from day to day, so there’s a challenge of finding the new tools, which would enable us to deal with this overload.

    As a response to this challenge we at Nodus Labs developed a new free online software tool Textexture.Com, which visualizes any text as a network and enables the user to use this interactive visualization to read through the text in a non-linear fashion. Using the network one can see the most relevant topics inside the text organized as distinctively colored clusters of nodes, their relationship to one another, and the most influential words inside the text, responsible for topic shifts. This way the user can navigate right into the topic of the text that is the most relevant to them and use the bigger (more influential) nodes to shift into another subject.

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  • Text Network Hamlet Reading

    We visualized Hamlet’s “to be or not to be” as a text network and then read it again using Alexis Jacomy’s GexfWalker. Whether it is a new reading of Shakespeare’s classic or a bunch of unrelated words is for you to decide, but at least it allows for polysingularity of text to be expressed more fully through following the word relations while staying loyal to the text’s original structure.

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  • Polysingularity of Text Expressions

    Italo Calvino once said that “writing is essentially a combinatorial exercise” and that “reading is a way of exercising the potentialities contained in the system of signs”. We propose a new way of reading using text network visuaization. It goes beyond the normal sequential organization of textual material and instead offers the reader to navigate through polysingularity of meanings present within the text. Created using Alexis Jacomy’s GexfWalker and Gephi software.

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  • Visualization of Text’s Polysingularity Using Network Analysis

    Figure 10: Most prominent communities in both texts.

    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.

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  • Identifying the Pathways for Meaning Circulation using Text Network Analysis

    In this work we propose a method and algorithm for identifying the pathways for meaning circulation within a text. This is done by visualizing normalized textual data as a graph and deriving the key metrics for the concepts and for the text as a whole using network analysis. The resulting data and graph representation are then used to detect the key concepts, which function as junctions for meaning circulation within a text, contextual clusters comprised of word communities (themes), as well as the most often used pathways for meaning circulation.

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