An evaluation of hundreds of thousands of tweets reveals the altering which means of the phrase “bot”
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Calling somebody a bot on social media as soon as meant you suspected they have been truly a bit of software program, however now using the phrase is shifting to grow to be an insult to somebody is human, say researchers.
Many efforts to detect social media bots use algorithms to attempt to determine patterns of behaviour which are extra frequent in automated accounts managed by computer systems, the standard which means of a bot, however their accuracy is questionable.
“Most recent research really focuses on the detection of social bots, which is problematic in itself because we have this ground truth problem,” says Dennis Assenmacher at Leibniz Institute for Social Sciences in Cologne, Germany, which means we don’t know if detections are correct.
To research, Assenmacher and his colleagues checked out how customers understand what’s a bot or not. They did so by taking a look at how the phrase “bot” was used on Twitter between 2007 and December 2022 (the social community modified its title to X in 2023, following its buy by Elon Musk), analysing the phrases that appeared subsequent to it in additional than 22 million English-language tweets.
The staff discovered that earlier than 2017, the phrase was often deployed alongside allegations of automated behaviour of the kind that might historically match the definition of a bot, reminiscent of “software”, “script” or “machine”. After that date, the use shifted.
“Now, 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,” says Assenmacher.
Whereas the reason for the shift is unclear, Assenmacher says it could possibly be political in nature. The staff checked out high-profile accounts adopted by every Twitter person, reminiscent of these of politicians and journalists, to categorise customers as left or right-leaning. It turned out that left-leaning customers have been extra more likely to accuse others of being bots, and those that have been accused have been extra more likely to be right-leaning.
“A potential explanation might be that media frequently reported about right-wing bot networks influencing major events like the [2016] US election,” says Assenmacher. “However, this is just speculation and would need confirmation.”
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