What is Entropic Poetry ?

People tend to think that poetry has nothing to give today. What is a poem supposed to give ? What is poetry for?

It’s no surprise that people who belong to a highly visual age of information consider poetry as an obsolete aesthetical form of text. Because, according to this new perception, any kind of creative work could be understood and accepted as art only if it has some audio-visual character. And text is allowed to participate in the artworks as a mere communication channel, which is actually just a boring necessity, as it is the case in subtitles. Consequently, books are considered to be the incompact antic media of knowledge transfer, which could be easily replaced by CDs and DVDs. Consisting of huge volumes of pure text, a book is regarded as something meaningful only if it contains some kind of useful, that is pragmatic information, or if it has the potential to become an interesting scenario for a future movie. So it seems that we have arrived at a new and audio-visual station after our long adventure through written text.

While investigating the current situation of written text by problematizing the notions of information, data and speed, Entropic poetry demonstrates an art of poetic reaction against today’s audio-visual pragmatism which ignores and sacrifices the text. Among many other possible ways, entropic poetry finds a meaningful way to demonstrate that poems/texts have both informative and audio-visual aspects. Benefiting from binary encoding’s neutrality against various data types, it constitutes a concrete text-image-sound unity. At the same time, regarding information

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theory, entropic poetry acts as a tool to measure the degree of complexity of poetic works, encouraging the poet to be more experimental. For example, dada would appear more entropic in general, when we would transform both dada poems and classical poems into entropic poetry. Moreover, entropic poetry could function as a means of textualizing any given image, and any given music, by applying the inverse-transformation. Thus one could be able to find an analogous textual representation for, say, Picasso’s Guernica or Beethoven’s Moonlight Sonata.

Some selected poems translated into the language of entropic poetry are shown below :

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The representations above belong – totally or partly – to the poems Paradise Lost, Book I (John Milton); Totenklage (Hugo Ball); A Lookless Cat-Black (Ece Ayhan); Tempo Denyot, Remix (Ozcan Turkmen); Tempo Denyot, Titanna Imperatrix Mundi (Ozcan Turkmen), respectively.

Since entropic equivalents of letters are language-dependent, the first two representations are based on the letter occurences in english language whereas the latter three representations are based on turkish-specific values. For the second poem (Totenklage) which is actually written in a universal language, english based values are given preference.

When interpreting the results, there is a single rule to apply which is very simple : The more red a

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representation gets, the more information the base-text contains. Thus the red, orange or yellow sections indicate the points where the text gets more entropic whereas the green, blue or purple parts point out the frequently used letters and punctuations. In other words, what we get by applying the entropic conversion is the “thermal map” of the text.

How does Entropic Poetry work?

In his famous article "The Mathematical Theory of Communication” (1949) which gave birth to “Information Theory”, Claude E. Shannon (1916-2001) defined a measure of entropy :

H = - pi logpi

where pi is the probability of i. Putting all its results in the field of electrical engineering aside, and using the base-2 logarithm, this formula gives us a measure of average information contained in a message, in bits. The information contained by a message X is understood as the amount of uncertainty that is eliminated by observation of X. Shannon information is appropriate for an unordered space like the space of alphabetic letters.

When we take a written text as the message, then the pi’s in the formula become frequencies of occurrences of different letters/words or letter/word pairs, triplets etc. Every text unit – letter (pairs) or word (pairs) – contains an information amount which is inversely proportional to the frequency of occurrence of that unit (pi), and the text as a whole contains an

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average amount of information of H bits. For example, if a text is measured to have an entropy of 2 bits, then one would use 2 bits in digital representation of each text-unit, and the whole message could be represented as a binary string which has a length of 2n (where n is the total number of text-units in that text). As a result, any communication channel with a capacity of transmitting 2 bits would be enough to transmit such a text.

Entropic poetry uses Shannon information to process poems as text messages containing information, that is it makes use of statistics about the frequencies of letter occurences. In my implementation of entropic poetry as a java program, I’ve simply used letters as text-units. There were two basic reasons for choosing letters instead of words or letter pairs/triplets : First of all, it’s hard to find accurate statistical values about the occurrence frequencies of letter pairs or words. Secondly, accuracy wasn’t my principal concern. I knew that there would be always problems with accuracy whatever method or frequency subset I might use. Rather I’ve focused on what we get by applying some entropic transformation than the accuracy of that transformation itself.

So I took advantage of two different statistics: For turkish letters and punctuations I extracted my own occurrence frequencies from one of my former essays on digital poetry, namely the Digital Poetry : Today’s Purgatory (2002). Among many others, that text seemed more suitable to me, since it could be said to have been written in a kind of mixed language. For english letters I used the statistics I found at http://lists.village.virginia.edu/lists_archive/Humanist/v05/0181.html which claims to cover “approximately 1 million words of real text”.

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The next step was to transform the source text into a Pm x n matrix, where m is the total number of lines we get after the elimination of the header line, the blank lines between the lines and epigraphs; and n is the character-length of the longest line, including spaces. The absent elements of the Pm x n matrix were filled with blanks. Then this Pm x n matrix is given a visual representation according to an entropy-to-color table based on rainbow spectrum, and by mapping the entropic equivalents of character elements into piano keys (MIDI notes between 21 and 107), it is given an audio representation.

As I’ve mentioned before, the characters of the text which are considered to have more entropy will appear red, orange or yellow, whereas the more frequent letters and punctuations such as spaces, E, A etc. will appear in colors of green, blue and purple when the program is run. Similarly, we will hear higher pitched sounds for characters which are seldom encountered in texts. The size of the output panel is fixed; so, longer texts will be represented in a more dense fashion.

Relations to Information Aesthetics

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The application of information theory into the field of aesthetics is not new. The philosophers M. Bense and A. Moles constructed an Information Aesthetics influenced by Shannon’s and Wiener’s Information Theory. Moreover, Information Theory was also influential in music theory circles during 1950-1960. For example, Leonard Meyer’s Emotion and Meaning in Music published in 1956 was influenced by Information Theory. In 1957, Brooks, Hopkins, Neumann and Wright published the results of their research under the title An Experiment in Musical Composition (IRE Transactions on Electronic Computers, Vol. 6, No. 1) which, after an analysis of the probabilities of notes occurring in various hymns, resulted in computer generated hymns. Another work to mention is composer James Tenney’s Ergodos.

So, what is the relation of entropic poetry to information aesthetics? First of all, this is an implementation of entropic poetry, thus it is an application of the information theory to poetry. Although this application is something new, it wasn’t the whole motivation behind the work. Aiming at demonstrating something similar to what Maxwell demonstrated with his well-known equations, I “demanded the impossible”, and tried to create a tool which would glue data of different nature, that is text, image and sound together. Being the common physical attribute of signals of any nature, that glue was “frequency”, and Shannon Information served as the tool to bridge the gap between analog and digital worlds. It is important to notice, however, that entropic poetry is not a mere continuation or a mere implementation of the ideas of information

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aesthetics. Information aesthetics is in search of an objective aesthetics, and benefits from information theory as a scientific method that is powerful enough to explain the artist’s influence over publikum. In other words, information aesthetics considers Shannon Information the criterium, the explanation, the goal and the result of the whole aesthetical process, whereas entropic poetry uses the information theory also in an ironical manner. It takes advantage of science to be able to say : “Hey! Poetry is more than what you see in it! It is full of information, and it has an audio-visual character! So are you sure you want to see poems like the ones created by Entropic Poetry Tool?”. At the same time, entropic poetry turns to the poet and asks: “Are you sure you can’t paint something different than this?”

Both a tool and an artwork - Entropic poetry is a reaction to the publikum and a warning to the poet.

Ozcan Turkmen, 01/03/2010 (revised)

Web References :

http://en.wikipedia.org/wiki/Information_theory

http://csml.som.ohio-state.edu/Music829D/Notes/

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Infotheory.html

http://lists.village.virginia.edu/lists_archive/Humanist/v05/0181.html

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