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Science Quickly

Celebrities Tweet Like Bots

Science Quickly

Scientific American

Science

4.2639 Ratings

🗓️ 5 August 2017

⏱️ 3 minutes

🧾️ Download transcript

Summary

Celebrity Twitter accounts look a lot like Twitter bots: They tweet regularly, follow relatively few people, and upload a lot of content. Christopher Intagliata reports.  Learn more about your ad choices. Visit megaphone.fm/adchoices

Transcript

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0:00.0

Understanding the human body is a team effort. That's where the Yachtel group comes in.

0:05.8

Researchers at Yachtolt have been delving into the secrets of probiotics for 90 years.

0:11.0

Yacold also partners with nature portfolio to advance gut microbiome science through the global grants for gut health, an investigator-led research program.

0:19.6

To learn more about Yachtolt, visit yawcp.co.j.jot.com.j, that's Y-A-K-U-L-T-C-O-J-P.

0:28.4

When it comes to a guide for your gut, count on Yacolt.

0:33.7

This is Scientific American's 60-second science. I'm Christopher in Taliatta.

0:39.0

Twitter has more than 300 million monthly active users, but researchers have estimated that between

0:44.8

about 30 million and 50 million of those are Twitter bots, automated accounts that do the

0:50.0

bidding of their code writing creators.

0:52.3

There could be newsbots and there could be spam bots.

0:55.2

Zafar Ghilani, a PhD student at the University of Cambridge in the UK.

0:59.2

Or there could be bots which are doing political infiltration, which is obviously bad,

1:04.3

or social infiltration, which could be bad.

1:06.5

Not all bots are bad, though.

1:08.1

Some are just geeky, like a bot that describes imaginary exoplanets,

1:11.6

or another that tweets only prime numbers.

1:14.6

It really depends on who the bot master is and what are the intentions, what are the motivations.

1:20.6

Galani and his colleagues built an algorithm to single out bots from human accounts

1:24.6

using factors like tweet frequency or content and how much users interacted

1:29.1

with other users. And the system was able to tell bot from human 86% of the time. But in the case

1:34.9

of celebrity accounts, people with more than 10 million followers, the bots and humans were harder

1:40.1

to tell apart. Because both tend to tweet with more scheduled regularity than the average human,

...

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