Social bot

Social bots are used for a large number of purposes on a variety of social media platforms, including Twitter, Instagram, Facebook, and YouTube. One common use of social bots is to inflate a social media user's apparent popularity, usually by artificially manipulating their engagement metrics with large volumes of fake likes, reposts, or replies. Social bots can similarly be used to artificially inflate a user's follower count with fake followers, creating a false perception of a larger and more influential online following than is the case.{{Cite journal |last1=Zhou |first1=Liying |last2=Jin |first2=Fei |last3=Wu |first3=Banggang |last4=Chen |first4=Zhi |last5=Wang |first5=Cheng Lu |date=2023-03-01 |title=Do fake followers mitigate influencers' perceived influencing power on social media platforms? The mere number effect and boundary conditions |url=https://www.sciencedirect.com/science/article/abs/pii/S0148296322010542 |journal=Journal of Business Research |volume=158 |pages=113589 |doi=10.1016/j.jbusres.2022.113589 |issn=0148-2963}} The use of social bots to create the impression of a large social media influence allows individuals, brands, and organizations to attract a higher number of human followers and boost their online presence. Fake engagement can be bought and sold in the black market of social media engagement.Omena, J. J., Chao, J., Pilipets, E., Kollanyi, B., Zilli, B., Flaim, G., ... & Del Nero, S. (2019). [https://www.researchgate.net/publication/339442015_Bots_and_the_black_market_of_social_media_engagement "Bots and the black market of social media engagement."] Digital Methods Initiative Wiki. Retrieved March 20, 2025.

Corporations typically use automated customer service agents on social media to affordably manage high levels of support requests.{{Cite book |last1=Xu |first1=Anbang |last2=Liu |first2=Zhe |last3=Guo |first3=Yufan |last4=Sinha |first4=Vibha |last5=Akkiraju |first5=Rama |chapter=A New Chatbot for Customer Service on Social Media |date=2017-05-02 |title=Proceedings of the 2017 CHI Conference on Human Factors in Computing Systems |chapter-url=https://dl.acm.org/doi/abs/10.1145/3025453.3025496 |series=CHI '17 |location=New York, NY, USA |publisher=Association for Computing Machinery |pages=3506–3510 |doi=10.1145/3025453.3025496 |isbn=978-1-4503-4655-9}} Social bots are used to send automated responses to users’ questions, sometimes prompting the user to private message the support account with additional information. The increased use of automated support bots and virtual assistants has led to some companies laying off customer-service staff.{{Cite news |date=2025-02-20 |title=Rogers lays off customer-service staff in multiple provinces |url=https://www.theglobeandmail.com/business/article-rogers-lays-off-customer-service-staff-in-multiple-provinces/ |access-date=2025-03-20 |work=The Globe and Mail |language=en-CA}}

Social bots are also often used to influence public opinion. Autonomous bot accounts can flood social media with large numbers of posts expressing support for certain products, companies, or political campaigns, creating the impression of organic grassroots support.{{Cite web |title=The influence of social bots |url=https://www.akademische-gesellschaft.com/en/research/topics/power-of-bots/the-influence-of-social-bots/%7BTSFE:baseUrl%7D |access-date=2022-03-01 |website=www.akademische-gesellschaft.com |language=en-EN}} This can create a false perception of the number of people who support a certain position, which may also have effects on the direction of stock prices or on elections.{{Cite web |title=What is a social media bot? {{!}} Social media bot definition |url=https://www.cloudflare.com/learning/bots/what-is-a-social-media-bot/ |access-date=2025-03-20 |website=www.cloudflare.com |language=en-us}}{{Cite web |last=Hu |first=Charlotte |title=How AI Bots Could Sabotage 2024 Elections around the World |url=https://www.scientificamerican.com/article/how-ai-bots-could-sabotage-2024-elections-around-the-world/ |access-date=2025-03-20 |website=Scientific American |language=en}} Messages with similar content can also influence fads or trends.{{Cite report |url=https://www.jstor.org/stable/resrep20399 |title=The New War of Ideas: Counterterrorism Lessons for the Digital Disinformation Fight |last=Frederick |first=Kara |date=2019 |publisher=Center for a New American Security}}

Many social bots are also used to amplify phishing attacks. These malicious bots are used to trick a social media user into giving up their passwords or other personal data. This is usually accomplished by posting links claiming to direct users to news articles that would in actuality direct to malicious websites containing malware.{{Cite book |last1=Shafahi |first1=Mohammad |last2=Kempers |first2=Leon |last3=Afsarmanesh |first3=Hamideh |chapter=Phishing through social bots on Twitter |date=December 2016 |title=2016 IEEE International Conference on Big Data (Big Data) |chapter-url=https://ieeexplore.ieee.org/document/7841038 |pages=3703–3712 |doi=10.1109/BigData.2016.7841038|isbn=978-1-4673-9005-7 }} Scammers often use URL shortening services such as TinyURL and bit.ly to disguise a link's domain address, increasing the likelihood of a user clicking the malicious link.{{Cite book |last1=Padmanabhan |first1=Sankar |last2=Maramreddy |first2=Prema |last3=Cyriac |first3=Marykutty |chapter=Spam Detection in Link Shortening Web Services Through Social Network Data Analysis |series=Advances in Intelligent Systems and Computing |date=2020 |volume=1079 |editor-last=Raju |editor-first=K. Srujan |editor2-last=Senkerik |editor2-first=Roman |editor3-last=Lanka |editor3-first=Satya Prasad |editor4-last=Rajagopal |editor4-first=V. |title=Data Engineering and Communication Technology |chapter-url=https://link.springer.com/chapter/10.1007/978-981-15-1097-7_9 |language=en |location=Singapore |publisher=Springer Nature |pages=103–118 |doi=10.1007/978-981-15-1097-7_9 |isbn=978-981-15-1097-7}} The presence of fake social media followers and high levels of engagement help convince the victim that the scammer is in fact a trusted user.

Social bots can be a tool for computational propaganda.{{Cite journal |last=Haile |first=Yirgalem A |date=2024-12-22 |title=The theoretical wedding of computational propaganda and information operations: Unraveling digital manipulation in conflict zones |url=https://journals.sagepub.com/doi/10.1177/14614448241302319 |journal=New Media & Society |language=EN |pages=14614448241302319 |doi=10.1177/14614448241302319 |issn=1461-4448}} Bots can also be used for algorithmic curation, algorithmic radicalization, and/or influence-for-hire, a term that refers to the selling of an account on social media platforms.

Bots have coexisted with computer technology since the earliest days of computing. Social bots have their roots in the 1950s with Alan Turing, whose work focused on machine intelligence with the development of the Turing Test. The following decades saw further progress made towards the goal of creating programs capable of mimicking human behavior, notably with Joseph Weizenbaum’s creation of ELIZA.{{Cite journal |last1=Ferrara |first1=Emilio |last2=Varol |first2=Onur |last3=Davis |first3=Clayton |last4=Menczer |first4=Filippo |last5=Flammini |first5=Alessandro |date=2016-06-24 |title=The rise of social bots |url=https://dl.acm.org/doi/10.1145/2818717 |journal=Commun. ACM |volume=59 |issue=7 |pages=96–104 |doi=10.1145/2818717 |issn=0001-0782|arxiv=1407.5225 }} Considered to be one of the first Chatbots, ELIZA could simulate natural conversations with human users through pattern matching. Its most famous script was DOCTOR, a simulation of a Rogerian psychotherapist that was programmed to chat with patients and respond to questions.{{Cite journal |last=Bassett |first=Caroline |date=2019-12-01 |title=The computational therapeutic: exploring Weizenbaum's ELIZA as a history of the present |url=https://link.springer.com/article/10.1007/s00146-018-0825-9 |journal=AI & Society |language=en |volume=34 |issue=4 |pages=803–812 |doi=10.1007/s00146-018-0825-9 |issn=1435-5655}}

With the growth of social media platforms in the early 2000s, these bots could be used to interact with much larger user groups in an inconspicuous manner. Early instances of autonomous agents on social media could be found on sites like MySpace, with social bots being used by marketing firms to inflate activity on a user’s page in an effort to make them appear more popular.{{Cite web |last=Errett |first=Joshua |date=2008-06-12 |title=Robots invade MySpace - NOW Magazine |url=https://nowtoronto.com/news/robots-invade-myspace/ |access-date=2025-03-24 |website=NOW Toronto |language=en-CA}}

Social bots have been observed on a large variety of social media websites, with Twitter being one of the most widely observed examples. The creation of Twitter bots is generally against the site’s terms of service when used to post spam or to automatically like and follow other users, but some degree of automation using Twitter’s API may be permitted if used for “entertainment, informational, or novelty purposes.”{{Cite web |title=Rules for Posting automated Tweets with Twitter Bots - Digital Inspiration |url=https://digitalinspiration.com/docs/twitter-bots/automated-tweet-policies |access-date=2025-03-24 |website=digitalinspiration.com |language=en}} Other platforms such as Reddit and Discord also allow for the use of social bots as long as they are not used to violate policies regarding harmful content and abusive behavior. Social media platforms have developed their own automated tools to filter out messages that come from bots, although they cannot detect all bot messages.{{Cite journal |last1=Efthimion |first1=Phillip |last2=Payne |first2=Scott |last3=Proferes |first3=Nicholas |date=2018-07-20 |title=Supervised Machine Learning Bot Detection Techniques to Identify Social Twitter Bots |url=https://scholar.smu.edu/datasciencereview/vol1/iss2/5 |journal=SMU Data Science Review |volume=1 |issue=2}}

File:Twitter bots 2016-11-13.png]]Due to the difficulty of recognizing social bots and separating them from "eligible" automation via social media APIs, it is unclear how legal regulation can be enforced. Social bots are expected to play a role in shaping public opinion by autonomously acting as influencers. Some social bots have been used to rapidly spread misinformation, manipulate stock markets, influence opinion on companies and brands, promote political campaigns, and engage in malicious phishing campaigns.{{Cite journal |last1=Gorwa |first1=Robert |last2=Guilbeault |first2=Douglas |date=2020 |title=Unpacking the Social Media Bot: A Typology to Guide Research and Policy |url=https://onlinelibrary.wiley.com/doi/10.1002/poi3.184 |journal=Policy & Internet |language=en |volume=12 |issue=2 |pages=225–248 |doi=10.1002/poi3.184 |arxiv=1801.06863 |issn=1944-2866}}

In the United States, some states have started to implement legislation in an attempt to regulate the use of social bots. In 2019, California passed the Bolstering Online Transparency Act (the B.O.T. Act) to make it unlawful to use automated software to appear indistinguishable from humans for the purpose of influencing a social media user's purchasing and voting decisions.{{Cite web |author1=Julius Cerniauskas |date=2024-06-11 |title=The legal and ethical implications of sharing the web with bots |url=https://www.techradar.com/pro/the-legal-and-ethical-implications-of-sharing-the-web-with-bots |access-date=2025-03-24 |website=TechRadar |language=en}} Other states such as Utah and Colorado have passed similar bills to restrict the use of social bots.{{Cite web |title=State Lawmakers Propose Regulating Chatbots |url=https://www.multistate.ai/updates/vol-46 |access-date=2025-03-24 |website=multistate.ai |language=en-US}}

The Artificial Intelligence Act (AI Act) in the European Union is the first comprehensive law governing the use of Artificial Intelligence.{{Cite journal |last=Butt |first=Junaid Sattar |date=March 2024 |title=Analytical Study of the World's First EU Artificial Intelligence (AI) Act, 2024 |url=https://www.researchgate.net/publication/384675254 |journal=International Journal of Research Publication and Reviews |volume=5 |issue=3 |pages=7343–7364 |doi=10.55248/gengpi.5.0324.0914 |via=ResearchGate}} The law requires transparency in AI to prevent users from being tricked into believing they are communicating with another human. AI-generated content on social media must be clearly marked as such, preventing social bots from using AI in a manner that mimics human behavior.{{Cite web |date=2025-01-04 |title=Filling social media with indistinguishable AI-bots is illegal with EU AI Act |url=https://blog.lukaszolejnik.com/filling-social-media-with-indistinguishable-ai-bots-is-illegal-with-eu-ai-act/ |access-date=2025-03-24 |website=Security, Privacy & Tech Inquiries}}

The first generation of bots could sometimes be distinguished from real users by their often superhuman capacities to post messages. Later developments have succeeded in imprinting more "human" activity and behavioral patterns in the agent. With enough bots, it might be even possible to achieve artificial social proof. To unambiguously detect social bots as what they are, a variety of criteria{{cite conference|last=Dewangan|first=Madhuri|author2=Rishabh Kaushal|title= SocialBot: Behavioral Analysis and Detection|book-title=International Symposium on Security in Computing and Communication|year=2016|doi=10.1007/978-981-10-2738-3_39|url=https://link.springer.com/chapter/10.1007/978-981-10-2738-3_39}} must be applied together using pattern detection techniques, some of which are:{{cite journal |last1=Ferrara |first1=Emilio |last2=Varol |first2=Onur |last3=Davis |first3=Clayton |last4=Menczer |first4=Filippo |last5=Flammini |first5=Alessandro |year=2016 |title=The Rise of Social Bots |journal=Communications of the ACM |volume=59 |issue=7 |pages=96–104 |doi=10.1145/2818717 |url=http://cacm.acm.org/magazines/2016/7/204021-the-rise-of-social-bots/fulltext|arxiv=1407.5225 |s2cid=1914124 }}

• cartoon figures as user pictures
• sometimes also random real user pictures are captured (identity fraud)
• reposting rate
• temporal patterns{{cite conference|last=Mazza|first=Michele|author2=Stefano Cresci|author3=Marco Avvenuti|author4=Walter Quattrociocchi|author5=Maurizio Tesconi|title= RTbust: Exploiting Temporal Patterns for Botnet Detection on Twitter|book-title=In Proceedings of the 10th ACM Conference on Web Science (WebSci '19)|year=2019|doi=10.1145/3292522.3326015|arxiv=1902.04506}}
• sentiment expression
• followers-to-friends ratio{{cite web|url=http://www.socialmediaexaminer.com/find-and-remove-fake-followers-from-twitter-and-instagram/|title=How to Find and Remove Fake Followers from Twitter and Instagram : Social Media Examiner}}
• length of user names
• variability in (re)posted messages
• engagement rate (like/followers rate)
• analysis of the time series of social media posts{{Cite journal |last1=Weishampel |first1=Anthony |last2=Staicu |first2=Ana-Maria |author2-link=Ana-Maria Staicu|last3=Rand |first3=William |date=2023-03-01 |title=Classification of social media users with generalized functional data analysis |journal=Computational Statistics & Data Analysis |volume=179 |pages=107647 |doi=10.1016/j.csda.2022.107647 |s2cid=253359560 |issn=0167-9473|doi-access=free }}

Social bots are always becoming increasingly difficult to detect and understand. The bots' human-like behavior, ever-changing behavior of the bots, and the sheer volume of bots covering every platform may have been a factor in the challenges of removing them.{{Cite journal |last1=Zago |first1=Mattia |last2=Nespoli |first2=Pantaleone |last3=Papamartzivanos |first3=Dimitrios |last4=Perez |first4=Manuel Gil |last5=Marmol |first5=Felix Gomez |last6=Kambourakis |first6=Georgios |last7=Perez |first7=Gregorio Martinez |date=August 2019 |title=Screening Out Social Bots Interference: Are There Any Silver Bullets? |url=https://ieeexplore.ieee.org/document/8808170 |journal=IEEE Communications Magazine |volume=57 |issue=8 |pages=98–104 |doi=10.1109/MCOM.2019.1800520 |s2cid=201623201 |issn=1558-1896}} Social media sites, like Twitter, are among the most affected, with CNBC reporting up to 48 million of the 319 million users (roughly 15%) were bots in 2017.{{Cite web |last=Newberg |first=Michael |date=10 March 2017 |title=As many as 48 million Twitter accounts aren't people, says study |url=https://www.cnbc.com/2017/03/10/nearly-48-million-twitter-accounts-could-be-bots-says-study.html |access-date=2022-11-22 |website=CNBC |language=en}}

Botometer{{cite web|url=http://botometer.org/|title=Botometer}} (formerly BotOrNot) is a public Web service that checks the activity of a Twitter account and gives it a score based on how likely the account is to be a bot. The system leverages over a thousand features.{{cite conference|last=Davis|first=Clayton A.|author2=Onur Varol|author3=Emilio Ferrara|author4=Alessandro Flammini|author5=Filippo Menczer|title= BotOrNot: A System to Evaluate Social Bots|book-title=Proc. WWW Developers Day Workshop|year=2016|doi=10.1145/2872518.2889302|arxiv=1602.00975}}{{cite conference|last=Varol|first=Onur|author2=Emilio Ferrara|author3=Clayton A. Davis|author4=Filippo Menczer|author5=Alessandro Flammini|title=Online Human-Bot Interactions: Detection, Estimation, and Characterization |book-title=Proc. International AAAI Conf. on Web and Social Media (ICWSM)|year=2017|url=https://aaai.org/ocs/index.php/ICWSM/ICWSM17/paper/view/15587}} An active method for detecting early spam bots was to set up honeypot accounts that post nonsensical content, which may get reposted (retweeted) by the bots.{{cite web|publisher=technologyreview.com|title=How to Spot a Social Bot on Twitter|quote=Social bots are sending a significant amount of information through the Twittersphere. Now there’s a tool to help identify them|date=2014-07-28 |url=https://www.technologyreview.com/s/529461/how-to-spot-a-social-bot-on-twitter/}} However, bots evolve quickly, and detection methods have to be updated constantly, because otherwise they may get useless after a few years.{{Cite journal |author1=Grimme, Christian |author2=Preuss, Mike |author3=Adam, Lena |author4=Trautmann, Heike |year=2017 |title=Social Bots: Human-Like by Means of Human Control? |journal=Big Data |language=en |volume=5 |issue=4 |pages=279–293 |arxiv=1706.07624 |doi=10.1089/big.2017.0044 |pmid=29235915 |s2cid=10464463}} One method is the use of Benford's Law for predicting the frequency distribution of significant leading digits to detect malicious bots online. This study was first introduced at the University of Pretoria in 2020.{{Cite journal |last1=Mbona |first1=Innocent |last2=Eloff |first2=Jan H. P. |date=2022-01-01 |title=Feature selection using Benford's law to support detection of malicious social media bots |url=https://www.sciencedirect.com/science/article/pii/S0020025521009695 |journal=Information Sciences |language=en |volume=582 |pages=369–381 |doi=10.1016/j.ins.2021.09.038 |hdl=2263/82899 |s2cid=240508186 |issn=0020-0255|hdl-access=free }} Another method is artificial-intelligence-driven detection. Some of the sub-categories of this type of detection would be active learning loop flow, feature engineering, unsupervised learning, supervised learning, and correlation discovery.

Some operations of bots work together in a synchronized way. For example, ISIS used Twitter to amplify its Islamic content by numerous orchestrated accounts which further pushed an item to the Hot List news,{{Cite book |last1=Giummole |first1=Federica |last2=Orlando |first2=Salvatore |last3=Tolomei |first3=Gabriele |title=2013 International Conference on Social Computing |chapter=Trending Topics on Twitter Improve the Prediction of Google Hot Queries |date=2013 |chapter-url=http://dx.doi.org/10.1109/socialcom.2013.12 |pages=39–44 |publisher=IEEE |doi=10.1109/socialcom.2013.12|isbn=978-0-7695-5137-1 |s2cid=15657978 }} thus further amplifying the selected news to a larger audience.{{Cite journal |last1=Badawy |first1=Adam |last2=Ferrara |first2=Emilio |date=2018-04-03 |title=The rise of Jihadist propaganda on social networks |url=http://dx.doi.org/10.1007/s42001-018-0015-z |journal=Journal of Computational Social Science |volume=1 |issue=2 |pages=453–470 |doi=10.1007/s42001-018-0015-z |arxiv=1702.02263 |s2cid=13122114 |issn=2432-2717}} This mode of synchronized bots accounts can be used as a tool of propaganda as well as stock markets manipulations.{{Cite journal |last1=Sela |first1=Alon |last2=Milo |first2=Orit |last3=Kagan |first3=Eugene |last4=Ben-Gal |first4=Irad |date=2019-11-15 |title=Improving information spread by spreading groups |url=http://dx.doi.org/10.1108/oir-08-2018-0245 |journal=Online Information Review |volume=44 |issue=1 |pages=24–42 |doi=10.1108/oir-08-2018-0245 |s2cid=211051143 |issn=1468-4527}}

Instagram reached a billion active monthly users in June 2018,{{Cite web |last=Constine |first=Josh |date=2018-06-20 |title=Instagram hits 1 billion monthly users, up from 800M in September |url=https://techcrunch.com/2018/06/20/instagram-1-billion-users/ |access-date=2022-11-24 |website=TechCrunch |language=en-US}} but of those 1 billion active users, it was estimated that up to 10% were being run by automated social bots. While malicious propaganda posting bots are still popular, many individual users use engagement bots to propel themselves to a false virality, making them seem more popular on the app. These engagement bots can like, watch, follow, and comment on the users' posts.{{Cite web |date=2021-08-15 |title=Instagram Promotion Service (Real Marketing) – UseViral |url=https://useviral.com/instagram/ |access-date=2022-11-24 |language=en-US}}

Around the same time, the platform achieved the 1 billion monthly user plateau. Facebook (Instagram and WhatsApp's parent company) planned to hire 10,000 to provide additional security to their platforms; this would include combatting the rising number of bots and malicious posts on the platforms.{{Cite web |date=July 18, 2018 |title=Instagram's Growing Bot Problem |url=https://www.theinformation.com/articles/instagrams-growing-bot-problem |access-date=2022-11-24 |website=The Information}} Due to increased security on the platform and the detection methods used by Instagram, some botting companies are reporting issues with their services because Instagram imposes interaction limit thresholds based on past and current app usage, and many payment and email platforms deny the companies access to their services, preventing potential clients from being able to purchase them.{{Cite web |last=Morales |first=Eduardo |date=2022-03-08 |title=Instagram Bots in 2021 — Everything You Need To Know |url=https://bettermarketing.pub/instagram-bots-in-2021-everything-you-need-to-know-b57fb0a3b8e9 |access-date=2022-11-24 |website=Medium |language=en}}

{{Main|Twitter bot}}

Twitter's bot problem is caused by the ease of creating and maintaining them. The ease of creating the account as and the many APIs that allow for complete automation of the accounts are leading to excessive amounts of organizations and individuals using these tools to push their own needs.{{Cite book |last1=Gilani |first1=Zafar |last2=Farahbakhsh |first2=Reza |last3=Crowcroft |first3=Jon |title=Proceedings of the 26th International Conference on World Wide Web Companion - WWW '17 Companion |chapter=Do Bots impact Twitter activity? |date=2017-04-03 |chapter-url=https://doi.org/10.1145/3041021.3054255 |location=Republic and Canton of Geneva, CHE |publisher=International World Wide Web Conferences Steering Committee |pages=781–782 |doi=10.1145/3041021.3054255 |isbn=978-1-4503-4914-7|s2cid=33003478 }} CNBC claimed that about 15% of the 319 million Twitter users in 2017 were bots; the exact number is 48 million. As of July 7, 2022, Twitter is claiming that they remove 1 million spam bots from their platform every day.{{Cite news |last1=Dang |first1=Sheila |last2=Paul |first2=Katie |date=2022-07-07 |title=Twitter says it removes over 1 million spam accounts each day |language=en |work=Reuters |url=https://www.reuters.com/technology/twitter-says-it-removes-over-1-million-spam-accounts-each-day-2022-07-07/ |access-date=2022-11-23}}

Some bots are used to automate scheduled tweets, download videos, set reminders and send warnings of natural disasters.{{Cite web |last=Azhar |first=Huzaifa |date=2021-12-10 |title=10 Best Twitter Bots You Should Follow in 2022 - TechPP |url=https://techpp.com/2021/12/10/best-twitter-bots/ |access-date=2022-11-24 |website=techpp.com |language=en-US}} Those are examples of bot accounts, but Twitter's API allows for real accounts (individuals or organizations) to use certain levels of bot automation on their accounts and even encourages the use of them to improve user experiences and interactions.{{Cite web |title=Twitter's automation development rules {{!}} Twitter Help |url=https://help.twitter.com/en/rules-and-policies/twitter-automation |access-date=2022-11-24 |website=help.twitter.com |language=en}}

In 2025, Meta announced it would be creating an AI product that helps users create AI characters on Instagram and Facebook, allowing these characters to have bios, profile pictures, generate and share "AI-powered content" on the platforms.{{Cite news |last1=Murphy |first1=Hannah |last2=Criddle |first2=Cristina |date=2024-12-27 |title=Meta envisages social media filled with AI-generated users |url=https://www.ft.com/content/91183cbb-50f9-464a-9d2e-96063825bfcf |access-date=2025-01-01 |work=Financial Times}}{{Cite web |last=Herrman |first=John |date=2024-12-31 |title=Meta's Big Bet on Bots |url=https://nymag.com/intelligencer/article/meta-wants-more-ai-bots-on-facebook-and-instagram.html |access-date=2025-01-02 |website=Intelligencer |language=en}}{{Cite web |author1=Kevin Okemwa |date=2024-12-30 |title="They'll have bio's and profile pictures": Meta is gearing up to unleash a wave of AI-powered personas, set to redefine Facebook's social engagement |url=https://www.windowscentral.com/software-apps/theyll-have-bios-and-profile-pictures-meta-is-gearing-up-to-unleash-a-wave-of-ai-powered-personas-set-to-redefine-facebooks-social-engagement |access-date=2025-01-02 |website=Windows Central |language=en}} Bot accounts managed by Meta began to be identified by the public around on January 1, 2025,{{Cite web |title=Threads |url=https://www.threads.net/@beingjanine_/post/DETOZhFStm-?xmt=AQGzkyUYy140OWwzS_UCdVU342Lt1FdMYI0NIv81gFrRMQ |access-date=2025-01-02 |website=www.threads.net}}{{Cite web |last=Sato |first=Mia |date=2025-01-03 |title=Meta's AI-generated bot profiles are not being received well |url=https://www.theverge.com/2025/1/3/24334946/meta-ai-profiles-instagram-facebook-bots |access-date=2025-02-12 |website=The Verge |language=en-US}} with social media users noting that they appeared to be unblockable by human accounts and came with blue ticks to indicate they had been verified by Meta as trustworthy profiles.{{Cite web |last=Growcoot |first=Matt |date=2025-01-06 |title=Meta Purges AI-Generated Facebook and Instagram Accounts Amid Backlash |url=https://petapixel.com/2025/01/06/meta-purge-ai-generated-facebook-and-instagram-accounts-amid-backlash/ |access-date=2025-02-12 |website=PetaPixel |language=en}}

SocialAI, an app created on September 18, 2024, was created with the full purpose of chatting with only AI bots without human interaction.{{Cite web |last=Davis |first=Wes |date=2024-09-17 |title=SocialAI: we tried the Twitter clone where no other humans are allowed |url=https://www.theverge.com/2024/9/17/24247253/social-ai-app-replace-humans-with-bots |access-date=2025-02-12 |website=The Verge |language=en-US}} Its creator was Michael Sayman, a former product lead at Google who also worked at Facebook, Roblox, and Twitter.{{Cite web |last=Ghosh |first=Shona |title=The 24-year-old whiz kid who was hired by Mark Zuckerberg then Google is leaving to work at Roblox |url=https://www.businessinsider.com/ex-facebook-google-michael-sayman-joins-roblox-2020-12 |access-date=2025-02-12 |website=Business Insider |language=en-US}} An article on the Ars Technica website linked SocialAI to the Dead Internet Theory.{{Cite web |last=Edwards |first=Benj |date=2024-09-18 |title="Dead Internet theory" comes to life with new AI-powered social media app |url=https://arstechnica.com/information-technology/2024/09/dead-internet-theory-comes-to-life-with-new-ai-powered-social-media-app/ |access-date=2025-02-12 |website=Ars Technica |language=en-US}}

{{Portal|Internet|Society|Politics|Psychology}}

• {{annotated link|Astroturfing}}
• {{annotated link|Chatbot}}
• {{annotated link|Dead Internet theory}}
• {{annotated link|Devumi}}
• {{annotated link|Enshittification}}
• {{annotated link|Fake news website}}
• {{annotated link|Ghost followers}}
• {{annotated link|Internet bot}}
• Moderator
• {{annotated link|Social spam}}
• {{annotated link|Sybil attack}}
• {{annotated link|Twitter bomb}}
• {{annotated link|Whispering campaign}}

{{reflist}}

• [https://comprop.oii.ox.ac.uk/ The Computational Propaganda Research Project] University of Oxford
• [https://www.cloudflare.com/learning/bots/what-is-a-social-media-bot/ What is a Social Media Bot? | Social Media Bot Definition] Cloudflare

{{Disinformation}}

{{Media and human factors}}

Category:Internet bots

Category:Social media

Category:Public relations

Category:Social influence

Category:Social information processing

Category:Mass media monitoring

Category:Internet manipulation and propaganda