This narrative poem tells the mock-heroic adventures of an unlikely antihero on an imaginary quest. As Bigelow describes the piece,
In “How They Brought the News from Paradise to Paterson,” a first-person speaker narrates his story (in heroic verse) as he swims from one end of a resort pool complex to another in search of what he thinks is more alcohol, but is in fact a journey to find his marriage
and himself. The poem plays with the epic and tragic within a setting stifled with consumerism and class separation.
The poem is structured as the monomyth, in which the speaker, while lounging at the Paradise pool bar in a 5-star resort in Barbados, overhears what he interprets as a call to adventure: the bar has run out of rum. Taking upon himself to embark upon a journey through the pool complex to find the god-like Concierge at the far end, whose “sage advice / and quick, imperious commands” would restore the flow of rum in Paradise.
This work consists of a web page with a selected unicode keyboard that allows people to enter symbols into a text submission box which can then be posted to Twitter under the @crashtxt account. Jim Punk is an alias for an anonymous net artist whose work embodies glitch aesthetics and pictorial uses of language and characters, as seen in ascii art. To be precise, this work is a tool for unicode art, strapped on to a social network as a mode for publication, but also as a constraint. It is also an invitation for errors, since compatibility and support for certain Unicode characters vary on different operating systems and browsers. To use this work to write texts for publication in Twitter is to engage a basic component for digital communication: the encoding of writing and its associated symbols in computational environments, which aligns it with some of the goals of Lettrism.
I invite you to explore, write, draw with this tool considering what can be written with this online keyboard, which might seem alien compared to a QWERTY keyboard but represents very human needs for symbolic communication beyond the most common 107 (or so) characters.
This bot data mines a 1% sample of the public Twitter stream to identify tweets that could be considered haiku. It then republishes the result, formatting it as can be seen above, and retweets the original in its Twitter account. The page the haikus are published in uses random background images of nature, a nod towards the seasonal reference so valued in this poetic tradition.
This “bot without organs” tweets quotes on an indeterminate schedule and frequency randomly chosen from Deleuze and Guattari’s writings. The generator occasionally punctuates the quotes with a short phrase in slang like “True dat!” This may not even be a bot, but a human being who tweets the results of a random quote search engine focused on their published texts.
This bot generates poetry by sifting through 10% of all Tweets, parsing them with a dictionary for the pronunciation data, and identifying the ones that happen to scan as iambic pentameter. It then organizes the tweets into rhyming couplets and publishes them in Twitter by retweeting the original postings. Finally, it aggregates them into the shape of a Shakespearean sonnet in a website (Pentametron.com) that offers a sequence of 14 sonnets. Every hour, a new couplet is posted, changing all 14 sonnets as one couplet enters the sequence of 98 couplets and the oldest couplet, the final volta, exits the collection.
This poetry generator uses the Wordnik library’s recent rhyming functionality as dataset suitable for creating rhyming couplets in the ’80s freestyle rap tradition.
Examining the source code reveals that the generating algorithm method is simple, but it’s nuanced enough to produce grammatical lines in that tradition. Kazemi wrote 57 line templates each of which was missing the last word and organized them into arrays by the part of speech of that missing word. The JavaScript program calls rhyming words from Wordnik, along with their parts of speech, calls up random lines from the arrays, and assembles the battle rap. There are two noteworthy twists on this procedure, the occasional variable within lines between male and female terms (“sistas” and “homies” for example), and the presence of a word filter, aptly named “badwords.txt,” which identifies and filters hateful or derogatory language.
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 generates a metaphor every two minutes (in spite of its name, since Twitter places limits on automated posting), and it is more than sufficient. The constraint provides a little breathing room to consider the metaphor before facing a new one. How does one approach this steady stream of conceptually challenging metaphors?
According to George Lakoff and Mark Johnson’s cognitive linguistic metaphor theory, a metaphor is a mental process of thinking of one conceptual domain in terms of another. Their method to study metaphor was to identify the source and target domains and map the linguistic expression of the metaphor across both. The poetic practice of the conceit or extended metaphor lends itself well to this kind of analysis, because it overtly explores the connection across both.
This poetic mashup Twitter bot places Walt Whitman in conversation with contemporary people expressing their frustrations in social networks. To be precise, he repurposes Darius Kazemi’s “Latour Swag” code to remix two different Twitter sources: @TweetsOfGrass and original tweets with the #fml hashtag.
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.
This mesmerizing work of observational poetry juxtaposes a generative haiku with a split-screen 6 minute looping video composed of short clips captured along the Tokaido line. Luers’ statement explains the concept in detail in the “About” page.
With our small cameras, smartphones and apps we document our travels. We capture and collect “haiku” moments, tokens of time and space, just as we always have, whether with pen and paper or the bulky camcorder. But with digital technology, we now store these moments as files in searchable databases. How do we use them? Do we try to find the narratives in the fragments or hunt for the suprising incongruities? Perhaps we only care about the isolated moment,the singular shot or sequence, which we “share” as soon as it has rendered. However we narrate experience, our devices and their databases remind us that there are always moments lost in any narrative retelling, always a different path through the data.
