Editing Internet bot (section)

==Social bots==
{{main|Social bot}}
Social bots are sets of algorithms that take on the duties of repetitive sets of instructions in order to establish a service or connection among social networking users. Among the various designs of networking bots, the most common are [[chat bot]]s, algorithms designed to converse with a human user, and social bots, algorithms designed to mimic human behaviors to converse with patterns similar to those of a human user. The history of social botting can be traced back to [[Alan Turing]] in the 1950s and his vision of designing sets of instructional code approved by the [[Turing test]]. In the 1960s [[Joseph Weizenbaum]] created [[ELIZA]], a natural language processing computer program considered an early indicator of artificial intelligence algorithms. ELIZA inspired computer programmers to design tasked programs that can match behavior patterns to their sets of instruction. As a result, natural language processing has become an influencing factor to the development of artificial intelligence and social bots. And as information and thought see a progressive mass spreading on social media websites, innovative technological advancements are made following the same pattern.{{fact|date=November 2022}}

[[File:Twitter bots 2016-11-13.png|thumb|Twitter bots posting similar messages during the [[2016 United States elections]]]]
Reports of political interferences in recent elections, including the 2016 US and 2017 UK general elections,<ref>{{Cite web|url=https://spectrum.ieee.org/how-political-campaigns-weaponize-social-media-bots|title=How Political Campaigns Weaponize Social Media Bots|last=Howard|first=Philip N|date=18 October 2018|website=IEEE Spectrum}}</ref> have set the notion of bots being more prevalent because of the ethics that is challenged between the bot's design and the bot's designer. [[Emilio Ferrara]], a computer scientist from the University of Southern California reporting on Communications of the ACM,<ref name="RiseOfSocialBots">{{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 }}</ref> said the lack of resources available to implement [[fact-checking]] and information verification results in the large volumes of false reports and claims made about these bots on social media platforms. In the case of Twitter, most of these bots are programmed with search filter capabilities that target keywords and phrases favoring political agendas and then retweet them. While the attention of bots is programmed to spread unverified information throughout the social media platforms,<ref>{{Cite journal|last1=Alessandro|first1=Bessi|last2=Emilio|first2=Ferrara|date=2016-11-07|title=Social Bots Distort the 2016 US Presidential Election Online Discussion|language=en|ssrn=2982233 |journal=First Monday}}</ref> it is a challenge that programmers face in the wake of a hostile political climate. The Bot Effect is what Ferrera reported as the socialization of bots and human users creating a vulnerability to the leaking of personal information and polarizing influences outside the ethics of the bot's code, and was confirmed by Guillory Kramer in his study where he observed the behavior of emotionally volatile users and the impact the bots have on them, altering their perception of reality.{{fact|date=November 2022}}