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.[citation needed] The automation of Twitter accounts is governed by a set of automation rules that outline proper and improper uses of automation.[2] Proper usage includes broadcasting helpful information, automatically generating interesting or creative content, and automatically replying to users via direct message.[3][4][5] Improper usage includes circumventing API rate limits, violating user privacy, spamming,[6] 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,[7] or posting helpful information,[8] although price changes introduced to the previously free API service in June 2023 resulted in many such accounts closing.[9]
Types
Positive influence
The @congressedits Twitter bot posted when Wikipedia articles were edited anonymously from IP addresses within the ranges assigned to the United States Congress
Many non-malicious bots are popular for their entertainment value. However, as technology and the creativity of bot-makers improves, so does the potential for Twitter bots that fill social needs.[10][11] @tinycarebot is a Twitter bot that encourages followers to practice self care, and brands are increasingly using automated Twitter bots to engage with customers in interactive ways.[12][13] One anti-bullying organization has created @TheNiceBot, which attempts to combat the prevalence of mean tweets by automatically tweeting kind messages.[14]
In June 2023, Twitter began charging $100 per month for basic access to its API, resulting in many entertainment bots being suspended or taken down.[9]
Concerns about political Twitter bots include the promulgation of malicious content, increased polarization, and the spreading of fake news.[15][16][17] A subset of Twitter bots programmed to complete social tasks played an important role in the United States 2016 Presidential Election.[18] Researchers estimated that pro-Trump bots generated four tweets for every pro-Clinton automated account and out-tweeted pro-Clinton bots 7:1 on relevant hashtags during the final debate. Deceiving Twitter bots fooled candidates and campaign staffers into retweeting misappropriated quotes and accounts affiliated with incendiary ideals.[19][20][21] Twitter bots have also been documented to influence online politics in Venezuela.[22] In 2019, 20% of the global Twitter trends were found to be created automatically using bots originating from Turkey. It is reported that 108,000 bot accounts were bulk tweeting to push 19,000 keywords to top trends in Turkey, to promote slogans such as political campaigns related to the 2019 Turkish local elections.[23]
In November 2022, Chinese bots coordinately flooded Twitter with garbage information (e.g. online gambling ads) so as to distract the users' attention away from the protests.[24] These bots, disguised as attractive girls, hashtagged the major cities in China.[25]
Fake followers
The majority of Twitter accounts following public figures and brands are often fake or inactive, making the number of Twitter followers a celebrity has a difficult metric for gauging popularity.[26] While this cannot always be helped, some public figures who have gained or lost huge quantities of followers in short periods of time have been accused of discreetly paying for Twitter followers.[27][28] For example, the Twitter accounts of Sean Combs, Rep Jared Polis (D-Colo), PepsiCo, Mercedes-Benz, and 50 Cent have come under scrutiny for possibly engaging in the buying and selling of Twitter followers, which is estimated to be between a $40 million and $360 million business annually.[27][28] Account sellers may charge a premium for more realistic accounts that have Twitter profile pictures and bios and retweet the accounts they follow.[28] In addition to an ego boost, public figures may gain more lucrative endorsement contracts from inflated Twitter metrics.[27] For brands, however, the translation of online buzz and social media followers into sales has recently come under question after The Coca-Cola Company disclosed that a corporate study revealed that social media buzz does not create a spike in short term sales.[29][30]
Identification
It is sometimes desirable to identify when a Twitter account is controlled by an internet bot.[31] Following a test period, Twitter rolled out labels to identify bot accounts and automated tweets in February 2022.[32][33]
Detecting non-human Twitter users has been of interest to academics.[31][34]
In a 2012 paper, Chu et al. propose the following criteria that indicate that an account may be a bot (they were designing an automated system):[1]
"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.
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.[35] Bots also post at more regular time gaps, for example, tweeting at 30-minute or 60-minute intervals.[35]
Indiana University has developed a free service called Botometer[36] (formerly BotOrNot), which scores Twitter handles based on their likelihood of being a Twitterbot.[37][38][39]
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[40] and in parallel to the owner of the account in some cases.[23]
Examples
The "Hourly Cosmos" Twitter bot in 2020
There are many different types of Twitter bots and their purposes vary from one to another. Some examples include:
@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.[41]
@CongressEdits and @parliamentedits posts whenever someone makes edits to Wikipedia from the United States Congress and United Kingdom Parliament IP addresses, respectively.[42] @CongressEdits was suspended in 2018 while @parliamentedits is still running.
@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.[43]
@DearAssistant sends auto-reply tweets responding to complex queries in simple English by utilizing Wolfram Alpha.[4]
@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.[45]
@everyword has tweeted every word of the English language. It started in 2007 and tweeted every thirty minutes until 2014.[46]
@nyt_first_said tweets every time The New York Times uses a word for the first time. It was created by artist and engineer Max Bittker in 2017.[47][48]
@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.[49]
@fuckeveryword was tweeting every word in the English language preceded by "fuck", but Twitter suspended it midway through operation because the account tweeted "fuck niggers".[50] @fckeveryword was created by someone else after the suspension to resurrect the task, which it completed in 2020.[51]
@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.[52] It went inactive following a brief promotion for Bear Stearns Bravo.
@infinite_scream tweets and auto-replies a 2–39 character scream.[53] At least partially inspired by Edvard Munch's The Scream,[54] it attracted attention from those distressed by the Presidency of Donald Trump[55] and bad news.[54]
@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.[56]
@RedScareBot tweets in the persona of Joseph McCarthy in response to Twitter posts mentioning "socialist", "communist", or "communism".[41]
@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.[58]
@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.[59]
Prevalence
In 2009, based on a study by Sysomos, Twitter bots were estimated to create approximately 24% of tweets on Twitter.[60] According to the company, there were 20 million, fewer than 5%, of accounts on Twitter that were fraudulent in 2013.[61] In 2013, two Italian researchers calculated 10 percent of total accounts on Twitter were "bots" although other estimates have placed the figure even higher.[62] One significant academic study in 2017 estimated that up to 15% of Twitter users were automated bot accounts.[63][64] A 2020 estimate puts the figure at 15% of all accounts or around 48 million accounts.[65]
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.[66] 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.[67]
Impact
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.[68][69][20][70] The social implications these Twitter bots potentially have on human perception are sizeable. 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.[71]Whether posts are perceived to be generated by humans or bots depends on partisanship, a 2023 study found.[72]
^ a bChu, Zi; Gianvecchio, Steven; Wang, Haining; Jajodia, Sushil (November 2012). "Detecting Automation of Twitter Accounts: Are You a Human, Bot, or Cyborg?". IEEE Transactions on Dependable and Secure Computing. 9 (6): 811–824. doi:10.1109/TDSC.2012.75.
^"Automation rules". Twitter Help Center. Archived from the original on December 5, 2017. Retrieved April 22, 2017.
^Martin Bryant (August 11, 2009). "12 weird and wonderful Twitter Retweet Bots". TNW. Archived from the original on August 10, 2018. Retrieved August 1, 2014.
^ a bProtalinski, Emil (March 8, 2013). "Dear Assistant: A Twitter bot that uses Wolfram Alpha to answer your burning questions". The Next Web, Inc. Archived from the original on April 20, 2019. Retrieved August 1, 2014.
^David Daw (October 23, 2011). "10 Twitter Bot Services to Simplify Your Life". PCWorld. Archived from the original on November 13, 2017. Retrieved May 31, 2012.
^"Twitter spam is out of control". The Verge. August 30, 2016. Archived from the original on July 31, 2018. Retrieved April 22, 2017.
^"Platform manipulation and spam policy". April 2022. Archived from the original on May 31, 2022. Retrieved May 28, 2022.
^Automation rules, November 3, 2017, archived from the original on December 5, 2017, retrieved May 28, 2022
^ a bBinder, Matt (June 24, 2023). "Twitter API changes crush @PossumEveryHour and other good bots". Mashable. Retrieved January 3, 2024.
^"The best Twitter bots of 2015". Quartz. Archived from the original on January 14, 2019. Retrieved May 1, 2018.
^"12 Weird, Excellent Twitter Bots Chosen by Twitter's Best Bot-Makers". November 9, 2015. Archived from the original on September 22, 2018. Retrieved February 21, 2020.
^"50 Innovative Ways Brands Use Chatbots - TOPBOTS". October 20, 2016. Archived from the original on April 25, 2019. Retrieved April 18, 2017.
^"This Self-Care Bot Makes Twitter a Healthier Place". Time. Archived from the original on October 5, 2018. Retrieved March 12, 2017.
^"Anti-bullying bot built to say nice things to 300 million people on Twitter". Telegraph.co.uk. Archived from the original on June 26, 2018. Retrieved April 13, 2017.
^Bessi, Alessandro; Ferrara, Emilio (November 3, 2016). "Social bots distort the 2016 U.S. Presidential election online discussion". First Monday. doi:10.5210/fm.v21i11.7090.
^Shao, Chengcheng; Giovanni Luca Ciampaglia; Onur Varol; Kaicheng Yang; Alessandro Flammini; Filippo Menczer (2018). "The spread of low-credibility content by social bots". Nature Communications. 9 (1): 4787. arXiv:1707.07592. Bibcode:2018NatCo...9.4787S. doi:10.1038/s41467-018-06930-7. PMC 6246561. PMID 30459415.
^"As Twitter moves to purge fake accounts, conservatives say they are being targeted - The Boston Globe". The Boston Globe. Archived from the original on July 9, 2018. Retrieved April 4, 2018.
^McGill, Andrew (June 2, 2016). "Have Twitter Bots Infiltrated the 2016 Election?". The Atlantic. Archived from the original on February 20, 2019. Retrieved April 18, 2017.
^"Bots and Automation over Twitter during the Third U.S. Presidential Debate" (PDF). Archived from the original (PDF) on November 9, 2016. Retrieved April 18, 2017.
^ a bPareene, Alex (February 28, 2016). "How We Fooled Donald Trump Into Retweeting Benito Mussolini". Archived from the original on June 27, 2016. Retrieved April 18, 2017.
^"Um, Did Kellyanne Conway Just Tweet a Hidden Neo-Nazi Message To a White Nationalist?". The Daily Banter. February 14, 2017. Archived from the original on May 17, 2017. Retrieved April 18, 2017.
^Morales, Juan S. (2020). "Perceived Popularity and Online Political Dissent: Evidence from Twitter in Venezuela". The International Journal of Press/Politics. 25: 5–27. doi:10.1177/1940161219872942.
^ a bElmas, Tuğrulcan; Overdorf, Rebekah; Özkalay, Ahmed Furkan; Aberer, Karl (2021). "Ephemeral Astroturfing Attacks: The Case of Fake Twitter Trends". 2021 IEEE European Symposium on Security and Privacy (EuroS&P). pp. 403–422. arXiv:1910.07783. doi:10.1109/EuroSP51992.2021.00035. ISBN 978-1-6654-1491-3.
^Davidson, Helen; Milmo, Dan (November 28, 2022). "Chinese bots flood Twitter in attempt to obscure Covid protests". TheGuardian.com. Archived from the original on November 28, 2022. Retrieved November 28, 2022.
^BRZESKI, PATRICK; RAHMAN, ABID (November 28, 2022). "Chinese Bots Inundate Twitter With Pornographic Spam Amid COVID Protests". The Hollywood Reporter. Archived from the original on November 28, 2022. Retrieved November 28, 2022.
^"Justin Bieber, Katy Perry, Rihanna, Taylor Swift and Lady Gaga: Who's faking it on Twitter?". Music Business Worldwide. January 31, 2015. Archived from the original on April 21, 2019. Retrieved April 13, 2017.
^ a b cPerlroth, Nicole (April 25, 2013). "Researchers Call Out Twitter Celebrities With Suspicious Followings". Bits Blog. Archived from the original on November 9, 2018. Retrieved April 13, 2017.
^ a b cPerlroth, Nicole (April 5, 2013). "Fake Twitter Followers Become Multimillion-Dollar Business". Bits Blog. Archived from the original on December 21, 2018. Retrieved April 13, 2017.
^"Buzzkill: Coca-Cola Finds No Sales Lift from Online Chatter". Archived from the original on April 22, 2019. Retrieved April 18, 2017.
^"Coca-Cola Says Social Media Buzz Does Not Boost Sales". Archived from the original on April 21, 2019. Retrieved April 18, 2017.
^ a bFerrara, Emilio; Varol, Onur; Davis, Clayton; Menczer, Filippo; Flammini, Alessandro (June 24, 2016). "The rise of social bots". Communications of the ACM. 59 (7): 96–104. doi:10.1145/2818717.
^Espósito, Filipe (September 9, 2021). "Twitter testing new labels to identify 'Good Bots' accounts and tweets". 9to5Mac. Archived from the original on September 27, 2022. Retrieved May 23, 2022.
^Perez, Sarah (February 17, 2022). "Twitter officially launches labels to identify the 'good bots'". TechCrunch. Retrieved May 23, 2022.
^Dewangan, Madhuri (2016). "SocialBot: Behavioral Analysis and Detection". Security in Computing and Communications. Communications in Computer and Information Science. Vol. 625. pp. 450–460. doi:10.1007/978-981-10-2738-3_39. ISBN 978-981-10-2737-6.
^ a bLu, Donna (May 2020). "AI can root out bots on Twitter". New Scientist. 246 (3280): 17. Bibcode:2020NewSc.246...17L. doi:10.1016/S0262-4079(20)30851-4.
^"Botometer". Archived from the original on May 26, 2020. Retrieved July 19, 2018.
^Davis, Clayton Allen; Varol, Onur; Ferrara, Emilio; Flammini, Alessandro; Menczer, Filippo (2016). "BotOrNot: A System to Evaluate Social Bots". Proceedings of the 25th International Conference Companion on World Wide Web - WWW '16 Companion. pp. 273–274. doi:10.1145/2872518.2889302. ISBN 978-1-4503-4144-8.
^Chu, Zi; Gianvecchio, Steven; Wang, Haining; Jajodia, Sushil (2010). "Who is tweeting on Twitter: Human, bot, or cyborg?". Proceedings of the 26th Annual Computer Security Applications Conference. pp. 21–30. doi:10.1145/1920261.1920265. ISBN 978-1-4503-0133-6.
^arXiv, Emerging Technology from the. "How to Spot a Social Bot on Twitter". Archived from the original on February 19, 2020. Retrieved April 18, 2017.
^Elmas, Tuğrulcan; Overdorf, Rebekah; Aberer, Karl (May 31, 2022). "Characterizing Retweet Bots: The Case of Black Market Accounts". Proceedings of the International AAAI Conference on Web and Social Media. 16: 171–182. doi:10.1609/icwsm.v16i1.19282.
^ a bChristine Erickson (July 22, 2012). "Don't Block These 10 Hilarious Twitter Bots". Mashable. Archived from the original on November 18, 2018. Retrieved December 28, 2012.
^Mosendz, Polly (July 24, 2014). "Congressional IP Address Blocked from Making Edits to Wikipedia". Archived from the original on March 28, 2016. Retrieved August 1, 2014.
^"The 8 best Twitter bots you aren't following". Digital Trends. August 2, 2013. Archived from the original on May 10, 2016. Retrieved May 24, 2016.
^Bonnie Burton (March 4, 2016). "Drumpf Twitterbot learns to imitate Trump via deep-learning algorithm". CNET. CBS Interactive. Archived from the original on March 16, 2019. Retrieved March 4, 2016.
^Judah, Sam; Ajala, Hannah (August 3, 2015). "The Twitter bot that 'corrects' people who say 'illegal immigrant'". BBC News. Archived from the original on February 13, 2019. Retrieved August 3, 2015.
^Dubbin, Rob (November 14, 2013). "The Rise of Twitter Bots". The New Yorker. Archived from the original on July 1, 2014. Retrieved March 9, 2014.
^Symonds, Alexandria (July 7, 2019). "When The Times First Says It, This Twitter Bot Tracks It". The New York Times. ISSN 0362-4331. Archived from the original on March 10, 2023. Retrieved March 10, 2023.
^"Do You Speak New York Times?". The New Yorker. March 7, 2023. Archived from the original on March 10, 2023. Retrieved March 10, 2023.
^Farrier, John. "Twitter Bot Pranks Gullible People with Hilariously Fake Facts". NeatoCMS. Archived from the original on May 17, 2018. Retrieved March 16, 2014.
^"The bot that tweeted "fuck" in front of every word was doomed from the start". Archived from the original on September 17, 2021. Retrieved September 17, 2021.
^"Fuck Every Word 2.0". Twitter. Archived from the original on March 15, 2022. Retrieved March 15, 2022.
^Adrian Chen (February 23, 2012). "How I Found the Human Being Behind Horse_ebooks, The Internet's Favorite Spambot". Gawker. Archived from the original on April 17, 2013. Retrieved May 4, 2012.
^Reed, Nora. "Cheap Bots, Done Quick!". cheapbotsdonequick.com. Archived from the original on October 3, 2017. Retrieved March 30, 2017.
^ a bAdkins, Ariel (February 26, 2017). "This Twitter Account Reacts To The Bad News In Your Timeline With an Infinite Scream". observer.com. New York Observer. Archived from the original on February 27, 2017.
^Grant, Megan (February 2017). "15 Totally Legit Ways To Deal When All You Want To Do Is Scream". bustle.com. Bustle. Archived from the original on March 30, 2017.
^Veale, Tony (2015). Game of Tropes: Exploring the Placebo Effect in Computational Creativity (PDF). ICCC-2015: Proceedings of the Sixth International Conference on Computational Creativity. Park City, Utah. Archived from the original (PDF) on August 13, 2015. Retrieved October 17, 2015.
^Max Read (April 30, 2012). "Weird Internets: The Amazing Found-on-Twitter Sonnets of Pentametron". Gawker. Archived from the original on March 21, 2014. Retrieved March 9, 2016.
^"This Self-Care Bot Makes Twitter a Healthier Place". Time. Archived from the original on October 5, 2018. Retrieved March 12, 2017.
^"DisinfoNews". Archived from the original on December 6, 2022. Retrieved February 2, 2023.
^Cashmore, Pete (August 6, 2009). "Twitter Zombies: 24% of Tweets Created by Bots". Mashable. Archived from the original on September 6, 2018. Retrieved March 19, 2014.
^D'onfro, Jillian (October 4, 2013). "Twitter Admits 5% Of Its 'Users' Are Fake". Business Insider. Archived from the original on March 1, 2021. Retrieved May 15, 2014.
^Woollacott, Emma. "Why fake Twitter accounts are a political problem". New Statesman. Archived from the original on February 25, 2021. Retrieved June 16, 2014.
^Varol, Onur; Emilio Ferrara; Clayton A. Davis; Filippo Menczer; Alessandro Flammini (2017). "Online Human-Bot Interactions: Detection, Estimation, and Characterization". Proc. International AAAI Conf. on Web and Social Media (ICWSM). Archived from the original on August 28, 2018. Retrieved July 19, 2018.
^Hill, Kashmir. "The Invasion of the Twitter Bots". Forbes. Archived from the original on February 12, 2019. Retrieved April 18, 2017.
^Rodríguez-Ruiz, Jorge; Mata-Sánchez, Javier Israel; Monroy, Raúl; Loyola-González, Octavio; López-Cuevas, Armando (April 2020). "A one-class classification approach for bot detection on Twitter". Computers & Security. 91: 101715. doi:10.1016/j.cose.2020.101715.
^"Study finds bot detection software isn't as accurate as it seems | MIT Sloan". November 30, 2023.
^"The Social Bot Fairy Tale - Tagesspiegel Background".
^actually, this source does not seem to support neither the claim of "prevalence" nor the "widespread" influence; Jay Hathaway merely portrays one amusing example of a troll-baiting tool: "This Twitter bot tricks angry trolls into arguing with it for hours". The Daily Dot. October 7, 2016. Archived from the original on October 19, 2018. Retrieved April 18, 2017.
^Collins, Ben (June 15, 2016). "A Twitter Bot Is Beating Trump Fans". The Daily Beast. Archived from the original on August 2, 2020. Retrieved July 8, 2018 – via www.thedailybeast.com.
^@5thdimdreamz (May 31, 2016). "@andrewmcgill 👽 perhaps 😏" (Tweet). Archived from the original on May 25, 2021. Retrieved April 8, 2022 – via Twitter.
^Spence, P.R.; Shelton, Ashleigh; Edwards, Chad; Edwards, Autumn (2013). "Is that a bot running the social media feed? Testing the differences in perceptions of communication quality for a human agent and a bot agent on Twitter". Computers in Human Behavior. 33: 372–376. doi:10.1016/j.chb.2013.08.013.
.png/1280px-Hourly_Cosmo_Twitter_Bot_(49690900513).png)
