Twitter bot

It is sometimes desirable to identify when a Twitter account is controlled by a bot.[7] In a 2012 paper,[1] Chu et al. propose the following criteria that indicate that an account may be a bot (they were designing an automated system):

• "Periodic and regular timing" of tweets;
• Whether the tweet content contains known spam; and
• The ratio of tweets from mobile versus desktop, as compared to an average human Twitter user.

Research shows that humans can view Twitter bots as a credible source of information.[8]

There are many different types of Twitter bots and their purposes vary from one to another. Some bots may tweet helpful material such as @EarthquakesSF (description below). In 2009, Twitter bots were estimated to create approximately 24% of tweets on Twitter.[9] Here are examples of some of the Twitter bots and how they interact with users on Twitter.

• @GNUTIEZ keeps track of the headlines and teasers of the major German online newspapers and tweets all changes made after an article is published.
• @HaiQuBot tweets short found poems, every 30 minutes, about the world under COVID-19 quarantine.
• @Zeitansage (German for speaking clock) tweeted the current time in 2009 and 2010 for about 330.000 times, every minute.
• @Betelgeuse_3 sends at-replies in response to tweets that include the phrase, "Beetlejuice, beetlejuice, beetlejuice". The tweets are sent in the voice of the lead character from the Beetlejuice film.[10]
• @BrEFTA Bot finds tweets which mention EFTA and Brexit and retweets them.
• @CongressEdits and @parliamentedits posts whenever someone makes edits to Wikipedia from the US Congress and UK Parliament IP addresses, respectively.[11]
• @DBZNappa replied with "WHAT!? NINE THOUSAND?" to anyone on Twitter that used the internet meme phrase "over 9000". The account began in 2011, and was eventually suspended in 2015, most likely a victim of its own success.[12]
• @DearAssistant sends auto-reply tweets responding to complex queries in simple English by utilizing Wolfram Alpha.[4]
• @DeepDrumpf is a recurrent neural network, created at MIT, that releases tweets imitating Donald Trump's speech patterns. It received its namesake from the term 'Donald Drumpf', popularized in the segment 'Donald Trump' from the show Last Week Tonight with John Oliver.[13]
• @DroptheIBot tweets the message, "People aren't illegal. Try saying 'undocumented immigrant' or 'unauthorized immigrant' instead" to Twitter users who have sent a tweet containing the phrase "illegal immigrant". It was created by American Fusion.net journalists Jorge Rivas and Patrick Hogan.[14]
• @everyword has tweeted every word of the English language. It started in 2007 and tweeted every thirty minutes until 2014.[15]
• @chssbot tweets historical chess matches every 4 hours.
• @factbot1 was created by Eric Drass to illustrate what he believed to be a prevalent problem: that of people on the internet believing unsupported facts which accompany pictures.[16]
• @fuckeveryword[17]
• @Horse_ebooks was a bot that gained a following among people who found its tweets poetic. It has inspired various _ebooks-suffixed Twitter bots which use Markov text generators (or similar techniques) to create new tweets by mashing up the tweets of their owner.[18] It went inactive following a brief promotion for Bear Stearns Bravo.
• @infinite_scream tweets and auto-replies a 2-39 character scream.[19] At least partially inspired by Edvard Munch's The Scream,[20] it attracted attention from those distressed by the Presidency of Donald Trump[21] and bad news.[20]
• @MetaphorMagnet is an AI bot that generates metaphorical insights using its knowledge-base of stereotypical properties and norms. A companion bot @MetaphorMirror pairs these metaphors to news tweets. Another companion bot @BestOfBotWorlds uses metaphor to generate faux-religious insights.[22]
• @Pentametron finds tweets incidentally written in iambic pentameter using the CMU Pronouncing Dictionary, pairs them into couplets using a rhyming dictionary, and retweets them as couplets into followers' feeds.[23]
• @RedScareBot tweets in the persona of Joseph McCarthy in response to Twitter posts mentioning "socialist", "communist", or "communism".[10]
• @tinycarebot promotes simple self care actions to its followers, such as remembering to look up from your screens, taking a break to go outside, and drink more water. It will also send a self care suggestion if you tweet directly at it.[24]

There are also families of related Twitter bots. For example, @LessicoFeed, @SpracheFeed, @SwedishFeed, @TraductionFeed, @VocabularioFeed, @WelshFeed each tweet an English word along with a translation every hour into Italian, German, Swedish, French, Spanish, and Welsh, respectively. The translations are crowdsourced[25] by volunteers and subscribers.

Detecting non-human Twitter users has been of interest to academics.[7][26] Indiana University has developed a free service called Botometer[27] (formerly BotOrNot), which scores Twitter handles based on their likelihood of being a Twitterbot.[28][29][30] One significant academic study estimated that up to 15% of Twitter users were automated bot accounts.[31][32] The prevalence of Twitter bots coupled with the ability of some bots to give seemingly human responses has enabled these non-human accounts to garner widespread influence.[33][34][35][36]

• Brexit bots (New Scientist)