This bot takes Tweet-sized snippets of text from movie reviews aggregated in Rotten Tomatoes, identifies nouns in the subject position, and replaces those with the names of right-wing pundits who appear regularly on the Fox News Channel, attaching the ironically intended hashtag #PraiseFOX. The bot was created essentially as joke for the politically charged comedy show The Colbert Report, as a reaction to the news that right-wing media had staff dedicated to refuting anything threatening to their ideological point of view, as explained by Stephen Colbert in the clip below.
These two bots generate responses to questions that have such subjective answers that no number of responses can really satisfy anyone, but do so in thought-provoking and amusing fashion.
“Is it art?” explores the challenge to the art world posed by the readymade Dada sculpture “Fountain,” attributed to Marcel Duchamp. His gesture of sending a standard urinal to be displayed in galleries as an art object, with a title and signed “R. Mutt” was very controversial and provoked questions about the nature of art. This bot is on an endless rant on the artistic or not artistic nature of different things, making statement such as:
Am I the only one who thinks transactions are not art?
— Is it art? (@IsItArtBot) June 12, 2014
This bot is “@thricedotted’s twittercat,” a virtual pet that interacts with them and its followers by doing the things cats do. Sometimes it meows or purrs, sometimes it describes actions, such as “*leaves dissected animals on the front step*” and
*gets into trouble* =^.^=
— glitch[FETA] ~(=^‥^) (@storyofglitch) June 12, 2014
These tweets occur on a seemingly random timer, but you can always get a reaction by interacting with it. For example, if you follow it on Twitter, it will follow you. If you address it, it responds.
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.
This bot tirelessly carries out a task too large for it to complete within a human lifetime: it explores an idea posed by Jorge Luis Borges in his story “The Library of Babel” of an infinite library full of books that contain a different combination of 23 letters and punctuation marks. “Each book contains four hundred ten pages; each page, forty lines; each line, approximately eighty black letters” (Schneider quotes Borges in the bot’s description). With this bot, Schneider illustrates the concept of this library via Twitter’s own constraints by tweeting 140 characters randomly chosen from 23 alphabetic characters, punctuation marks, and spaces. The result is pure language noise. . . or is it?
This bot tirelessly applies a principle described by Betteridge’s law of headlines, which states that “Any headline which ends in a question mark can be answered by the word no.” This has become a kind of litmus test for sloppy and sensationalist journalism, and the bot relentlessly applies by detecting question headlines in Twitter by newspapers, magazines, and journals and retweeting the headline with the answer: “No.” Or in Eppink’s words:
The Answer Is No serves a public purpose by watching Twitter for instances of journalistic uncertainty and answering them for the benefit of the publication and its readers.
This bot randomly tweets suggestions sent to it based on a simple constraint: two 4-letter words to be tattooed onto the knuckles of the hands and juxtaposed. The resulting tweets show both versatility and imagination– and is a popular creative constraint in tattoo circles, as we can see in collections such as this one. By tweeting the words in uppercase letters, it focuses on the language of the tattoos, de-emphasizing potential graphical information.
— Knuckle Tat (@knuckle_tat) June 8, 2014
Visit this link to read its most popular tweets.
To celebrate Allison Parrish’s achievement– getting her bot @everyword to complete its 7 year tour-de-force of tweeting every word in the English language in alphabetical order, every 30 minutes– this entry will briefly examine 12 bots inspired and followed by @everyword. If you’ve never heard of this, you may want to read this earlier entry in which I analyzed the bot from an e-poetic perspective. Here are some comments on the bots, in the order they appear in the list of bots followed by @everyword.
- @fuckeveryword – Every good work deserves a worthy parody. This bot mimics @everyword in every way, but adds “fuck” before each word. It must have a shorter dictionary, because it will be done fucking the English language by 2017.
- @everybrendan – This bot is supposedly “twittering every Brendan name in Project Gutenberg” but I’m not sure how that produces the output it tweets. (Update: it’s created by Leonard Richardson and documented here -thanks for the heads up, Tully)I suspect it’s as profoundly weird as this other project by Brendan Atkins.
- @everyletter – With a data set of 26 letters, this self explanatory bot completed its mission in about 3 minutes. It has 142 followers and has been retweeted and favorited extensively.
- @everycolorbot – This bot by Colin Bayer is tweets hourly a randomly selected color from the RGB color spectrum, which contains 16,777,216 different colors. It is a wonderful way to discover colors that we may not have precise names for, and it is developing an enthusiastic following.
- @languagepix – operates like @everyword, but also tweets the first image it finds on a Google Image search for that word. The word and picture pairings are generally illustrative, often surprising, and occasionally absurd.
- @tokiale – This bot clones @everyword but in Toki Pona.
- @everyarabicword – This bot implements @everyword in Arabic and should complete its task in 2019.
- ALL LEMMATA (@eveywilliwaw) – This bot by Liam Cooke already tweeted all 2600 words “consisting only of straight lines.” What a wonderful graphical constraint!
- @PowerVocabTweet – Allison Parrish describes this bot as “a procedural exploration in a genre I like to call ‘speculative lexicography’—basically, @everyword‘s dada cousin.” Follow it to enhance your vocabulary with nonsense words with plausible definitions.
- @everyunicode – Ramsey Nasser’s bot gives the @everyword treatment to every character in the Unicode 6.2 standard, which contains 1,114,112 characters and should take 63 years to complete. For a compressed expression of a similar context, see Jörg Piringer’s Unicode video.
- @defineeveryword – This bot by Mike Dory bravely attempted to define every word tweeted by @everyword until it broke on “urinalysis” on February 21, 2014.
- @iederwoord – John Schop’s Dutch version of @everyword.
There is something irresistible about a project with a clear beginning and an ending because we can build a narrative around it. As I write this entry, @everyword is tweeting away its last few words and every single one of them is retweeted, favorited, and replied to dozens of times. The excitement and suspense on what will be the last word is palpable and people are drawing connections between the word and the bot’s context.
You're ending with our beginnings, word. 🙁 RT @everyword: zygotic
— southpaw (@nycsouthpaw) June 7, 2014
But more important than the excitement of the moment is the inspiration that this simple bot has offered in carrying out its absurd, celebrated task. You know you’re on to something when you’re imitated, remixed, parodied, and extended.
Congratulations to Allison Parrish and @everyword for completing its task and thank you for the inspiration!
Every three hours, this bot tweets approximately 100 characters (about 20 words) of language written by William Blake, but not exactly. The tweets are recognizably Blake’s, but there’s something odd about them, as if he was performing some kind of automatic writing or Surrealist automatism to compose those texts. He wasn’t, but in a way this bot is doing it for him, to show us some of the underlying structures William Blake’s poetry and prose.
André Breton defined Surrealism as “pure psychic automatism, by which an attempt is made to express, either verbally, in writing or in any other manner, the true functioning of thought. The dictation of thought, in the absence of all control by the reason, excluding any aesthetic or moral preoccupation.” The Surrealists were interested in finding an artistic expression that revealed a higher reality than our bourgeois consciousness would allow.
“BillBlakeBot” uses a markov chain generator that analyzes the David Erdman revised edition of The Complete Poetry and Prose of William Blake (1988) to determine the statistical likelihood that a word will follow another. It then uses that lexicon and probabilities to generate phrases and sentences that mimic Blake’s style, even if the results don’t make sense. Roger Whitson discusses his bot and markov chains in great detail in this ICR 2013 presentation, concluding with some provocative questions:
I think it adds another level to what it means to “read” Blake. Can we read these tweets as having relevance to Blake’s work? Is it simply nonsense? Literally, it might be, but I feel algorithms like this one complicate some of those questions in fascinating ways.
When we read Blake’s texts, we read the results of hours of carefully crafted language, revised and edited exhaustively before etching them in copper plates to produce his famous illuminated books. These texts are the result of very conscious and deliberate creative process applied to his mystical visions and other sources of inspiration. To use a markov chain generator to cut across his life’s oeuvre reveals patterns of style that Blake was probably unaware of. Beyond its utility as form of distant reading, its poetic output is worth reading closely to analyze the textures of Blake’s language beyond semantics. @autoblake gives us access to a surreal Blake, of interest to scholars and enthusiasts alike.
pangs of adoration. The Lovers night bears on my pure transparent breast. The Eagles at her house arriv'd.
— BillBlakeBot (@autoblake) June 2, 2014
Coda: Interested in creating a Twitter bot from your favorite author’s work? Roger Whitson published the source code in GitHub.
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What’s the topic and title for your next academic conference paper?
If you were interested in submitting a proposal to The Digital Games Research Association (DiGRA) 2014 Conference but weren’t sure what to focus on, this bot was the one to follow because it tweets a suggestion every 15 minutes. And even though the deadline has passed, this may serve as a source of inspiration for research in game studies by performing a kind of brute force search for ideas.