editor’s note: i’m still giggling as i type this. maybe it’s an uncomfortable giggle. maybe it’s because i know how ridiculous and insane this realm is. i did have an interesting and rather disturbing experience today. i came up to an intersection and was not thinking about anything other than driving. as i look at the surrounding cars, suddenly i hear and feel in my body “oh my god i really am surrounded by bots”. that part of me – deep within the solar plexus. then i had this flash of a vision – i could see this milky yellow colored grids of energy above 2 cars – coming into their heads. wow i DID NOT expect nor ask to see that. it was there and gone in a flash. was it real? fake? whatever it was – it felt real to me. drove home and shook it off. maybe i laugh reading this title because more than likely many of these accounts were actually real humans not spouting the current narrative….or maybe because bots are not just programs behind a computer screen – they are also in beings that look like humans. and since all of us have been infected w/the virus, we have ALL been subject to such manipulation……
******
The five best ways to detect fake social-media accounts.
Twitter recently took drastic action as part of an effort to slow the spread of misinformation through its platform, shutting down more than two million automated accounts, or bots.
But Twitter shuttered only the most egregious, and obvious, offenders. You can expect the tricksters to up their game when it comes to disguising fake users as real ones.
It’s important not to be swayed by fake accounts or waste your time arguing with them, and identifying bots in a Twitter thread has become a strange version of the Turing test. Accusing posters of being bots has even become an oddly satisfying way to insult their intelligence.
Advances in machine learning hint at how bots could become more humanlike. IBM researchers recently demonstrated a system capable of conjuring up a reasonably coherent argument by mining text. And Google’s Duplex software also shows how AI systems can learn to mimic the nuances of human conversation.
But technology might also provide a solution. In 2015 the Defense Advanced Research Projects Agency ran a contest on Twitter bot detection. Participants trained their systems to identify fake accounts using five key data points. The resulting systems are far from perfect (the best worked about 40 percent of the time), but the efforts reveal how best to spot a bot on Twitter. We may come to rely on these signals much more.
- User profile
The most common way to tell if an account is fake is to check out the profile. The most rudimentary bots lack a photo, a link, or any bio. More sophisticated ones might use a photo stolen from the web, or an automatically generated account name. - Tweet syntax
Using human language is still incredibly hard for machines. A bot’s tweets may reveal its algorithmic logic: they may be formulaic or repetitive, or use responses common in chatbot programs. Missing an obvious joke and rapidly changing the subject are other telltale traits (unfortunately, they are also quite common among human Twitter users). - Tweet semantics
Bots are usually created with a particular end in mind, so they may be overly obsessed with a particular topic, perhaps reposting the same link again and again or tweeting about little else.
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