Quickmap twitter bot
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It gets even more complicated when you account for the fact that Twitter is a global platform, but the current handle-generating algorithm can only create names with Roman characters and numbers. But that means that some new people on Twitter can end up looking like bots. Roth says that having auto-handles is a frictionless way to get people onto Twitter right away, without asking them to come up with a catchy name on their own. Most of the time, Twitter’s name-generating algorithm creates handles with first names and a string of numbers. We're assigning people handles that people believe are bots, but those are actually real people on the other end of the interactions,” said Roth. “I’ll raise my hand on behalf of Twitter and say, this one’s on us. This is a commonly accepted shorthand for spotting a fake account, presumably because automatically generating multiple accounts is easier with auto-assigned handles. One of the first ways we all learned to identify bots is an account with the telltale string of jumbled letters and numbers.
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More on how they do that, below, plus four truths you should know about bots.įirst truth: Don’t assume an account with a peculiar name must be a bot. Roth’s team measures influence through impressions, or the number of people who see a Tweet. He says it’s not the number of bots, (around 5%, a number Twitter reports quarterly) but the impact they have on the conversation. Even after identifying bots, the task of taking down fake accounts can resemble a game of whack-a-mole.īut Roth - who has worked on the safety team since 2014, forever in Twitter years - keeps the big picture in mind.
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Sometimes the team works with outside experts like investigative journalists to crack sophisticated campaigns. These are real people whose job it is to figure out the more complicated questions of whether an account is automated, a real person being paid to behave like a bot, or a real person who just resembles a bot.
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The second, and perhaps more important line of defense, is a forensic team of investigators. They train algorithms to recognize common patterns of malicious activity these automatically challenge between 5 to 10M accounts a week. The first way the integrity team sniffs out bots is through machine learning. But the bots that the platform integrity team deals with are generally fake accounts deliberately created to distort information or manipulate people on Twitter. (Twitter also rolled out labels for political candidates in late 2019). Twitter just launched a label for "good bots" as part of an effort to provide more context for accounts you may interact with. One of the teams, the platform integrity team, is tasked with sorting humans from robots (although they can’t help you if you’re a robot and you don’t know it).
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Yoel Roth is the Head of Site Integrity for Twitter, overseeing the multiple teams that write and enforce the rules around spam, bots, misinformation, disinformation, and more. So Common Thread sat down with Twitter’s resident bot expert to understand the problem and clear up misconceptions about bots on Twitter. How do you tell if someone on Twitter is a person or a robot?Ī recent internal survey of daily people on Twitter across four countries revealed that their greatest concern when using the platform is that “there are too many bots or fake accounts.”