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

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

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

To learn more about Yachtolt, visit yawcult.co.

.jp. That's Y-A-K-U-L-T.C-O.J-P. When it comes to a guide for your gut, count on Yacolt.

This is Scientific Americans' 60-second science. I'm Karen Hopkin.

You can tell a lot about people's general state of mind based on their social media feeds.

Are they always tweeting about their biggest peaves or posting picks of particularly cute kitties?

Well, in a similar fashion, researchers are turning to Twitter for clues about the overall happiness of entire geographic communities.

What they're finding is that regional variation in the use of common phrases produces predictions that don't always reflect the local state of well-being.

But removing from their analyses just three specific terms, good, love, and LOLL,

greatly improves the accuracy of the methods.

We're living in a crazy COVID-19 error, and now more than ever, we're using social media

to adapt to a new normal and reach out to the friends and family that we can't meet face-to-face.

Kokeal Jedka studies computational linguistics at the National University of Singapore.

But our words aren't useful just to understand what we as individuals think and feel.

They're also useful clues about the community we live in.

One of the simpler methods that many scientists use to parse the data

involves correlating words with positive or negative emotions. But when those tallies are compared

with phone surveys that assess regional well-being, Jedka says they don't paint an accurate

picture of the local zeitgeist. To find out why, Jedka and her colleague, Johannes Eichstadt of Stanford University,

analyzed billions of tweets from around the United States, and they found that among the most

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