Poetry Chains and Collocation Nets are two intertwined projects that investigate the 1955 edition of Emily Dickinson’s complete poems through various interactive animated navigations of collocated words. As such, they perform what Samuels and McGann term “experimental analyses.” Each of the visualizations displays a different presentation of her work. Poetry Chains begins with two words and attempts to find a chain of words in a specified number of lines that connects them together, displaying them as it succeeds. Collocation Nets begins with a single word centered in the middle of the screen. When the user selects the word, a random selected of its collocations pops out in a surrounding ring. Any of those words can be selected, which results in collocations of that word appearing. A user can toggle into an ambient mode of this visualization that automatically eventually cycles through all of the words, forever.
These visualizations offer a continuously dynamic remapping of Dickinson’s work. The deformations present new opportunities for interpretation, some of which may lend themselves to successful insights, and others which might be ludicrous, or merely bland. Each of the visualizations performs this remapping in different ways. The Poetry Chain effectively runs a kind of smoothing operation, an averaging filter, by treating her entire corpus as a single poem. Additionally, it uses a depth-search algorithm to get between two points within the corpus, performing a non-linear “hopscotch” (with a poetic rather than narrative destabilization). The Collocation Net completely disassembles the corpus into individual words and links them together, not grammatically, but instead by a frequency metric that correlates words by the likelihood of their appearing together within the same line. While it is unclear what exactly the interpretive value of these remapping offers, it is interesting to think of them in relation to, or perhaps as a differentiation from, visualization projects utilizing the methods of information visualization or visual analytics. In those fields, it is assumed that the raw data is inherently atomic, and that the goal of the project is to enable users to recombine the data in different ways in order to facilitate new revealing and new interpretation, or what Peter Pirolli and Stuart Card term “knowledge crystallization.” That is, they allow the user to create models by the synthesis and analysis of data, through which hypotheses may be generated and then either validated or falsified. A recent article by Ben Shneiderman reframes the products of information visualization projects as creativity support tools, where the goal of such a tool is to facilitate novel ideas and new perspectives. Poems however, as noted in Samuels and McGann’s article, are not simply composed of irreducible raw data. Instead, the meaning in some sense is the raw data. But this meaning lives in the interaction between the text and the reader, and cannot be extracted, simplified, summarized, or evaluated in any direct way.
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