Twitter bot

A Twitter bot is a type of software bot that controls a Twitter account via the Twitter API.^[1] The social bot software may autonomously perform actions such as tweeting, retweeting, liking, following, unfollowing, or direct messaging other accounts.^[2] The automation of Twitter accounts is governed by a ^[3]set of automation rules that outline proper and improper uses of automation.^[4] Proper usage includes broadcasting helpful information, automatically generating interesting or creative content, and automatically replying to users via direct message.^[5]^[6]^[7] Improper usage includes circumventing API rate limits, violating user privacy, spamming,^[8] and sockpuppeting. Twitter bots may be part of a larger botnet. They can be used to influence elections and in misinformation campaigns.

Twitter's policies do allow non-abusive bots, such as those created as a benign hobby or for artistic purposes,^[9] or posting helpful information,^[10] although price changes introduced to the previously free API service in June 2023 resulted in many such accounts closing.^[11]

"Periodic and regular timing" of tweets;

Whether the tweet content contains known ; and

spam

The ratio of tweets from mobile versus desktop, as compared to an average human Twitter user.

It is sometimes desirable to identify when a Twitter account is controlled by an internet bot.^[33] Following a test period, Twitter rolled out labels to identify bot accounts and automated tweets in February 2022.^[34]^[35]

Detecting non-human Twitter users has been of interest to academics.^[33]^[36]

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):

Emilio Ferrara at the University of Southern California used artificial intelligence to identify Twitter bots. He found that humans reply to other tweets four or five times more than bots and that bots continue to post longer tweets over time.^[37] Bots also post at more regular time gaps, for example, tweeting at 30-minute or 60-minute intervals.^[37]

Indiana University has developed a free service called Botometer^[38] (formerly BotOrNot), which scores Twitter handles based on their likelihood of being a Twitterbot.^[39]^[40]^[41]

Recent research from EPFL argued that classifying a Twitter account as bot or not may not be always possible because hackers take over human accounts and use them as bots temporarily or permanently^[42] and in parallel to the owner of the account in some cases.^[25]

@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 film.^[43]

Beetlejuice

and @parliamentedits posts whenever someone makes edits to Wikipedia from the United States Congress and United Kingdom Parliament IP addresses, respectively.^[44] @CongressEdits was suspended in 2018 while @parliamentedits is still running.

@CongressEdits

@DBZNappa replied with "WHAT!? NINE THOUSAND?" to anyone on Twitter that used the phrase "over 9000." The account began in 2011, and was eventually suspended in 2015.^[45]

internet meme

@DearAssistant sends auto-reply tweets responding to complex queries in simple English by utilizing .^[6]

Wolfram Alpha

@DeepDrumpf is a , 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.^[46]

recurrent neural network

@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.

[47]

@everyword has tweeted every word of the English language. It started in 2007 and tweeted every thirty minutes until 2014.

[48]

@nyt_first_said tweets every time uses a word for the first time. It was created by artist and engineer Max Bittker in 2017.^[49]^[50]

The New York Times

@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.

[51]

@fuckeveryword was tweeting every word in the English language preceded by "fuck", but Twitter suspended it midway through operation because the account tweeted "fuck ".^[52] @fckeveryword was created by someone else after the suspension to resurrect the task, which it completed in 2020.^[53]

niggers

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.^[54] It went inactive following a brief promotion for Bear Stearns Bravo.

@Horse ebooks

@infinite_scream tweets and auto-replies a 2–39 character scream. At least partially inspired by Edvard Munch's The Scream,^[56] it attracted attention from those distressed by the Presidency of Donald Trump^[57] and bad news.^[56]

[55]

@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.

[58]

@Pentametron finds tweets incidentally written in using the CMU Pronouncing Dictionary, pairs them into couplets using a rhyming dictionary, and retweets them as couplets into followers' feeds.^[59]

iambic pentameter

@RedScareBot tweets in the persona of in response to Twitter posts mentioning "socialist", "communist", or "communism".^[43]

Joseph McCarthy

@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.

[60]

@DisinfoNews Disinformation News Aggregator automatically retweets tweets that shares news articles or scientific work related to disinformation, bots or trolls from experts relevant to those topics.

[61]

There are many different types of Twitter bots and their purposes vary from one to another. Some examples include:

Prevalence[edit]

In 2009, based on a study by Sysomos, Twitter bots were estimated to create approximately 24% of tweets on Twitter.^[62] According to the company, there were 20 million, fewer than 5%, of accounts on Twitter that were fraudulent in 2013.^[63] In 2013, two Italian researchers calculated 10 percent of total accounts on Twitter were "bots" although other estimates have placed the figure even higher.^[64] One significant academic study in 2017 estimated that up to 15% of Twitter users were automated bot accounts.^[65]^[66] A 2020 estimate puts the figure at 15% of all accounts or around 48 million accounts.^[67]

A 2023 MIT study found that third-party tools used to detect bots may not be as accurate as they are trained on data being collected in simplistic ways, and each tweet in these training sets then manually labeled by people as a bot or a human.^[68] Already in 2019 German researchers scrutinized studies that were using Botswatch and Botometer, dismissing them as fundamentally flawed and concluded that (unlike spam accounts) there is no evidence that "social bots" even exist.^[69]

Impact[edit]

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.^[70]^[71]^[22]^[72] The social implications these Twitter bots potentially have on human perception are sizeable according to a study published by the ScienceDirect Journal. Looking at the Computers as Social Actors (CASA) paradigm, the journal notes, "people exhibit remarkable social reactions to computers and other media, treating them as if they were real people or real places." The study concluded that Twitter bots were viewed as credible and competent in communication and interaction making them suitable for transmitting information in the social media sphere.^[73] Whether posts are perceived to be generated by humans or bots depends on partisanship, a 2023 study found.^[74]