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  1. Tweet Haikus

    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. (Source: Leonardo Flores, I ♥ E-Poetry)

    Hannelen Leirvåg - 09.05.2013 - 21:04

  2. @KarlMarxovChain

    The Karl Marxov Chain responds to a word that users (or Pereira) seed it to guide its search through Karl Marx’s publications, as described. When it gets the seed word, it finds it in the text and takes not the next word, but the next two words. The first two words of this 3-gram are first two words of the tweet. It then takes not the last of these words, but the last two and searches the text for that pair of words. Then, of all of the times that those words appear together, it picks one at random, adds the last word to the chain, and then moves up a word. The result is that the probabilities are a bit more constricted, meaning that the tweet conforms a bit more closely to the original text, meaning it ends up sounding a bit more like normal English. The bot also cheats a bit and tries to make “complete” sentences (start with a word that has an initial capital in the source text and end with a period), but it’s not always successful. The source texts are also not the cleanest in the world, so it sometimes hiccups and tosses out typographical gibberish. (Source: Leonardo Flores, I ♥ E-Poetry)

    Hannelen Leirvåg - 09.05.2013 - 21:23