NSA Prism Bot

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@NSA_PRISMbot

Description: An automated parody twitter account pretending to be associated with Prism. This bot does multiple things such as flagging tweets that contain words like ‘bomb’. It also spies on people logging on to various web apps and doing searches, tweeting their name and location. It also snoops on private emails and Google docs.

Type: spying, twitter, scraping, parody

Example tweet:

"Mr. Bxxxx Lxxxx of Agustinaford, New Mexico logged into Skydrive from 31.545° N, -159.041° E."

”***FLAG*** @Bxxxx mentioned “hostage” on Twitter. ***FLAG***”

Followers: 80+

Tweets: 400+

Designer: unknown

Interview with Henry Cooke

I’ve interviewed Henry Cooke a creative developer of fascinating bots amongst other things. I wanted to know more about his methods and thoughts on bots for the benefit of botology, and thankfully he delivered us some great responses below.

1. Declare your bots, what are their twitter handles, and which is your favourite? 
Most of the bots I run are based off of the same codebase. I call them “mimemorphs” in homage to the Philter Phactory's Infomorphs, which were the inspiration for my starting to fiddle with bots in the first place. There's a list of all the currently running mimeomorphs here. They’re fairly simple 2-gram Markov bots which learn vocabulary from a specific Twitter user (or group of users) and generate new utterances every so often. Most of them shadow friends of mine who asked for a tame spambot or people we thought worth / would appreciate an automatic parody.
Actually, my current favourite is @MundaneBond, which isn’t a mimeomorph. It’s barely even a bot; it’s just tweeting things from a list some friends & I compiled when we were having a silly day. It just makes me laugh :)
My favourite mimeomorphs are probably the loversBen found a couple of Twitter accounts which appear to belong to two people having an online love affair. Their own tweets tail off, but we set up a couple of mimeomorphs to learn the vocabularies of the two of them and continue the affair indefinitely on the internet (well, in theory. There Are Some Bugs).
 
There’s also The Landlord, but he’s a whole different story…
 

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r_bash4d

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@r_bash4d

Description: Bot designed to mirror and mash-up the designer’s twitter account. I suspect this is with markov algorithm set to an n-gram of 2 as the sentences are often nonsensical..

Type: personal, twitter, markov, double

Example tweet:

"Crunch by Two Tornados fly Over by Metrist is indistinguishable from 2001 that a Dark room speakers at work I’ll be paying for some."

Followers: 60+

Tweets: 3500+

Designer: Ben Bashford @bashford

engineered by: Henry Cooke @prehensile

PlzCrack

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@ PlzCrack

Description: A bot that will crack password hashes for you. Tweet it a n MD5, MD5(MD5), SHA-1, SHA-2, MySQL, NTLM, LM, MD2, MD4, RipeMD160, or WHIRLPOOL hash, and it will respond with the cracked password. I think it does this by parsing the hash to crackstation.net. Initiated 14/12/12

Type: respond, utility, password, repetitive, twitter

Example tweet:

"It is a sha1 hash of "lolowned". @TXXX"

Followers: 70+

Tweets: 40+

Designer: unknown

More: Crack Station

The birthplace of twitter spambots

Technology Review provides a great insight into who and how millions of twitter spam-bots are possibly created. One part of the bot making process that cannot be automated is the opening of an account. This job gets outsourced to ‘Mechanical Turks’ on crowdsourcing sites such as Amazon’s mechanical turk marketplace. Once the twitter profile is set up, the login details get passed on to the service that sells twitter followers. In a way, it is an automated process, if you count these mechanical turks as now being a link in the algorithm’s chain. The following is quoted from here.

Some of the work is a little shady. One person describing himself as a sociologist paid Hamilton a few cents to create a “believable” Twitter account. Her creation,Luke Lynch, who uses the handle @luke_daredevil, says he is “the eldest of four children” and a fan of rugby and pizza. For her character, whose photo she plucked off Google, Hamilton was required to post one believable tweet, choosing “The performance at BET Awards was popping.” 

The experience left Hamilton “wondering what that was all about.”

That fake Twitter account appears to be part of a wider spam network established by people associated with the social network View.io, possibly to recruit members. Unknown others have since take over the Luke Lynch identity, which has emitted a series of raunchy comments and stock quotes in Indian rupees. (View.io’s founder, Felix Chan, didn’t respond to a request for comment.)

“Ugh!” said Kulkarni after hearing how his MobileWorks software was being used. “We do try to police the spambots.” He says inexperienced workers might not recognize “spammy” jobs, calling it a “cyberliteracy issue.” But the problem isn’t new. Two years ago, researchers at New York University estimated that 41 percent of all jobs posted to Mechanical Turk were for generating spam, generating clicks on ads, or influencing search engine results (see “How Mechanical Turk Is Broken”).

architizer:

A Tweetbot that Generates Architecture From Your Tweets

The creative tweetbot @Tweet2form designed by Andrew Heumann transforms a cube according to a series of operations you tweet at it, and then tweets a picture of the resulting form. There are currently 10 formal operations that the bot understands:

Kim Kierkegaardashian

@ KimKierkegaard

Description: Bot that possibly uses Markov chains to mash-up the philosophy of Søren Kierkegaard with the tweets and observations of reality-TV celebrity Kim Kardashian. However given the success of each tweet I suspect a human moderates the feed selecting the best sentences.

Type: celebrity, twitter, mash-up, Markov

Example tweet:

"What if everything in life were a misunderstanding, what if laughter were really tears? Scared LOL !!"

Followers: 56,000+

Tweets: 90+

Designer: unknown

First Tweet: 28th June 2012 

"Hyun Ju Kim‘s TweetBot is a robotic spider that senses your presence and speaks to you, quoting sad, lonely passages from Kim’s own journal."

FanDumb

@ FanDumb

Description: Bot that finds twitter users that send way too many tweets in a day to a celebrity account, and names and shames them. One twitter abuser per day.

Type: celebrity, twitter, tweet number monitor, data

Example tweet:

"Lance Armstrong (@lancearmstrong) received over 114 tweets yesterday from @XXXXX"

Followers: 600+

Tweets: 15,000+

Designer: Nathan Fanaro @natefanaro

More: fan dumb me page

Caps Cop

@capscop

Description: A bot that finds tweets that are ALL IN CAPS and responds with a witty pre-written joke about caps abuse. The bot also has some hashtag commands to request info, and the website goes even further such as listing people that use all-caps too often.

Type: caps, twitter, reply, snitch, caps finder

Example tweet:

"@xxxxx On Twitter no one can hear you scream. Pipe down and turn your caps lock off."

Followers: 14,000+

Tweets: 950,000+

Designer: Nathan Fanaro @natefanaro

More: caps cop page