The three bots reviewed in this entry all carry out essentially the same technique– they create a tweet based on the juxtaposition of material from two different sources– yet produce output that feels quite different. The reasons for this are partly thematic, partly due to the data source, and partly because of the way the join the juxtaposed elements.
An important early bot that uses this technique is Ranjit Bhatnagar’s @Pentametron, which retweets iambic pentameter tweets joined by end rhyme and creating surprisingly cohesive and occasionally humorous couplets. Juxtaposition is also a poetic technique that became prominent with Modernism and is a central strategy in Ezra Pound’s poetry and poetics. This entry will analyze “Two Headlines” by Darius Kazemi, “Dreams, juxtaposed” by Allison Parrish, and “And Now Imagine” by Ivy Baumgarten.
This bot is “brute-forcing an episode from [Thomas Pynchon’s novel] Gravity’s Rainbow” by tweeting the words “you never did the Kenosha kid” with different punctuation every two hours. The bot description links to a Language Log entry that explains the episode– basically about a man who, under the effects of sodium amytal, goes on “an obsessive meditation on alternative possible analyses of the six-word sequence ‘you never did the kenosha kid.'” Inspired by the algorithm described here, Darius Kazemi created a bot that seeks all the possible combinations of that word sequence with punctuation (and appropriate capitalization). The result is a tour-de-brute-force of different syntactic structures and meanings that can emerge from this simple string of words. Try reading the following tweets out loud.
Este bot es “forzar brutalmente un episodio de [la novela de Thomas Pynchon] Gravity’s Rainbow” al twittear las palabras “nunca hiciste al chico Kenosha” con diferente puntuación cada dos horas. La descripción del bot se vincula a una entrada del Registro de idiomas que explica el episodio, básicamente sobre un hombre que, bajo los efectos del amytal sódico, continúa “una meditación obsesiva sobre posibles análisis alternativos de la secuencia de seis palabras, nunca hizo el kenosha kid.'” Inspirado por el algoritmo descrito aquí, Darius Kazemi creó un bot que busca todas las combinaciones posibles de esa secuencia de palabras con puntuación (y mayúsculas apropiadas).El resultado es un tour-de-brute-force de diferentes estructuras sintácticas y significados que pueden surgir de esta simple cadena de palabras. Intenta leer los siguientes tweets en voz alta.
This bot is a stand-in for Kazemi at the Game Developer’s Conference happening at the time of this posting in San Francisco, because he will not be able to attend for the first time in 10 years. So instead of pining away on Twitter as #GDC tweets flood his stream, he created a bot so his friends could have the pleasure of his company in their own streams, which as we know, is almost as good as his being there. If that were all this piece was, it would be little more than a Kazemi-themed Twitter equivalent of this:
This poetry generator uses the Wordnik library’s recent rhyming functionality as dataset suitable for creating rhyming couplets in the ’80s freestyle rap tradition.
The result has the form and texture of rap without some of its color, which probably for the best, since it lacks the context of a human rapper (warts and all) to deploy such forceful language. The range of vocabulary in the Wordnik library produces results so varied that the result feels like nerdcore hip hop, as in the lines generated above, particularly:
I’m smooth, you’ll never catch me acting Boolean
Way I rock the mic you know I’m born Tennessean
If the raps seem too formulaic, it bears to consider that freestyle rap battles were made possible by formal constraints and were a competitive expression of orality. In Orality and Literacy, Walter J. Ong discusses the tradition of oral performance as distinct from verbatim (word-by-word) memorization, in the context of Parry’s study of The Illiad.
were made up not simply of word-units but of formulas, groups of words for dealing with traditional materials, each formula shaped to fit into a hexameter line. The poet had a massive vocabulary of hexameterized phrases. With his hexameterized vocabulary, he could fabricate correct metrical lines without end, so long as he was dealing with traditional materials (57).
This algorithm simulates this process with 8-9 syllable line templates that produce lines of approximately 11 syllables when the word has been added. The line templates are also focused on the traditional materials of rap battles, including agonistic language and braggadocio. As with a live performance, these raps are intended to be apprehended as a whole rather than carefully scrutinized line by line, paying close attention only to memorable lines.
As with “Metaphor-a-Minute!” Kazemi encodes this social dimension for identifying particularly successful couplets. Users can share couplets they like through Twitter by simply pressing a button, which generates a tweet identified with the #rapbot hashtag and a link back to the generator.
So I recommend reading the generated rap songs, as well as Kazemi’s essay “Making a Rapbot,” and sharing the lines you enjoy the most, proof of Kazemi’s “equation for making a cool textual generator: randomness + formulaic writing = hilarity.”
This Twitter bot produces a mashup of the “Bruno Latourbot” and original tweets that use the #swag hashtag. Kazemi describes the selection algorithm in detail in this excerpt from his blog posting about the creation of this bot.
Basically how it works is I get the last 100 Twitter search results for “#swag” that also contain the word “and”. Then I grab the last 100 tweets from @LatourBot. I take every #swag tweet that’s not an RT and push it to an array. I take every @latourbot tweet that has “and” or “,” in it, and push it to an array. Then I say there’s a 50% chance it will be latour-then-swag, and 50% that it will be swag-then-latour. If Latour comes first, I take a random Latour tweet from the array and take all the text up to the “and” or the “,”. Then I take a random swag tweet and take the text after the “and” in it. Then I do latour + ” and ” + swag. There you go.