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A recent trend in digital humanities has been the development of new visualization tools to aid analyzing and understand of poetry. Historically, poetry has been analyzed and understood from a literary, data driven viewpoint of the syntactic and semantic elements of the texts at hand. Recent work, as is evident in the referenced texts has contrarily focused on a more qualitative, linguistic, and even graphical analysis of poetic literature.

The authors of the three abstracts all have in common that they extract features, key elements, like, margin size, width, height, spacing of text, syntax, rhyme, structure of the narrative, the organization of the poem, the language elements, etc. These features are used by the different tools to graphically represent the corresponding poems and help to visually analyze and compare them. After organizing all of this information, they are able to combine those features via pattern recognition.

It is at this point that their tools differ in their approach and motivation. Houston et al [1] use their recognized patterns to find clusters of poems which help them in their analysis of large corpora of literary work, for example of the Victorian era. Their tool enables them to identify significant trends and patterns in the graphical design of Victorian books, and also find out which texts, including previously lesser or even not all studied ones, are similar to other works from the same era, and thus representative to this era, rather than simply anecdotal.

On the other hand, Abdul-Rahman et al [2] map their features along a 26 dimensional space, allowing for the end user to decide which dimensions to display in the tool. The dimensions correspond to each of the features, or attributes which the authors defined as relevant to the analyzed poems, such as meter, sound, tone or rhyme. Here also, the authors perform a pattern recognition, enabling them further to not only compare poems with each other, but also allowing them to place the poems in their historical, societal and technological context.

Lastly, Meneses et al [3] take the approaches of the other two groups one step further, not only analyzing poems according to certain features and patterns, but also allowing poets to directly interact with the tool, and even other writers and readers, in real time. Or in other words, a framework that affords a symbiotic relationship between writing and visualization a poem. As an author writes new poetry, the visualization of it gives direct feedback to him, allowing to also understand the writing process from a unique new viewpoint.

Even though each of the groups of authors uses their respective tools for different motivations, what they all have in common is the use of visualization technology to get a better understanding of poetry.

References

  1. Houston, Natalie M. Audenaert, Neal.  “Reading the Visual Page of Victorian Poetry” Digital Humanities 2013. July 2013. http://dh2013.unl.edu/abstracts/ab-274.html
  2. Abdul-Rahman, Alfie. Coles, Katharine. Lein, Julie. Wynne, Martin. “Reading Freedom and Flow: A New Approach to Visualizing Poetry” Digital Humanities 2013. July 2013 http://dh2013.unl.edu/abstracts/ab-143.html
  3. Meneses, Luis.  Furuta, Richard. Mandell, Laura. “Ambiances: A Framework to Write and Visualize Poetry” Digital Humanities 2013. July 2013 http://dh2013.unl.edu/abstracts/ab-365.html
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