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<\/div>An analysis of millions of tweets reveals the changing meaning of the word \u201cbot\u201d<\/p>\n
Svet foto\/Shutterstock<\/p>\n<\/div>\n<\/figcaption><\/figure>\n<\/p>\n
Calling someone a bot on social media once meant you suspected they were actually a piece of software, but now the use of the word is shifting to become an insult to someone you know is human, say researchers.<\/p>\n
Many efforts to detect social media bots use algorithms to try to identify patterns of behaviour that are more common in automated accounts controlled by computers, the traditional meaning of a bot, but their accuracy is questionable.<\/p>\n
\u201cMost recent research really focuses on the detection of social bots, which is problematic in itself because we have this ground truth problem,\u201d says Dennis Assenmacher<\/a> at Leibniz Institute for Social Sciences in Cologne, Germany, meaning we don\u2019t know if detections are accurate.<\/p>\n To investigate, Assenmacher and his colleagues looked at how users perceive what is a bot or not. They did so by looking at how the word \u201cbot\u201d was used on Twitter between 2007 and December 2022 (the social network changed its name to X in 2023, following its purchase by Elon Musk<\/a>), analysing the words that appeared next to it in more than 22 million English-language tweets.<\/p>\n <\/p>\n The team found that before 2017, the word was usually deployed alongside allegations of automated behaviour of the type that would traditionally fit the definition of a bot, such as \u201csoftware\u201d, \u201cscript\u201d or \u201cmachine\u201d. After that date, the use shifted.<\/p>\n \u201cNow, the accusations have become more like an insult, dehumanising people, insulting them, and using this as a technique to deny their intelligence and deny their right to participate in a conversation,\u201d says Assenmacher.<\/p>\n While the cause of the shift is unclear, Assenmacher says it could be political in nature. The team looked at high-profile accounts followed by each Twitter user, such as those of politicians and journalists, to classify users as left or right-leaning. It turned out that left-leaning users were more likely to accuse others of being bots, and those who were accused were more likely to be right-leaning.<\/p>\n \u201cA potential explanation might be that media frequently reported about right-wing bot networks influencing major events like the [2016] US election,\u201d says Assenmacher. \u201cHowever, this is just speculation and would need confirmation.\u201d<\/p>\n Topics:<\/p>\n<\/section><\/div>\n