Curiosity Daily

Earth Is Greener Than Before, Job-Matching with Your Tweets, and Why Blue Means Sad

Episode Summary

Learn about how AI and Twitter could help you find the perfect job, and how the world is actually a greener place than it was 20 years ago. We’ll also answer a listener question about why we use the color “blue” to say we’re sad. Job-Matching with Your Tweets by Kelsey Donk Sources: Robot career advisor: AI may soon be able to analyse your tweets to match you to a job | The Conversation — https://theconversation.com/robot-career-advisor-ai-may-soon-be-able-to-analyse-your-tweets-to-match-you-to-a-job-128777  The Vocation Map (interactive) | Marian-Andrei Rizoiu — http://www.rizoiu.eu/documents/research/resources/Vocation_Map_Interactive.html   Social media-predicted personality traits and values can help match people to their ideal jobs | PNAS December 26, 2019 116 (52) 26459-26464; first published December 16, 2019 — https://www.pnas.org/content/116/52/26459  Earth Is Greener Than Before by Kelsey Donk Sources: Human Activity in China and India Dominates the Greening of Earth, NASA Study Shows | NASA — https://www.nasa.gov/feature/ames/human-activity-in-china-and-india-dominates-the-greening-of-earth-nasa-study-shows  China and India lead in greening of the world through land-use management | Chen, C., Park, T., Wang, X. et al. China and India lead in greening of the world through land-use management. Nat Sustain 2, 122–129 (2019) doi:10.1038/s41893-019-0220-7 — https://www.nature.com/articles/s41893-019-0220-7  Story 3 by Ashley Hamer (Listener question from Becky and Britni) Sources: Chaucer and the Country of the Stars: Poetic Uses of Astrological Imagery — https://curiosity.im/2NOyLIB  blue (adj.1) | Online Etymology Dictionary — https://www.etymonline.com/word/blue?ref=etymonline_crossreference#etymonline_v_13636  Drunk and dirty | BBC — http://www.bbc.co.uk/languages/yoursay/lost_for_words/german/drunk_and_dirty.shtml  Philip, Gill. (2006). Connotative Meaning in English and Italian Colour-Word Metaphors. Metaphorik. 10. — https://www.researchgate.net/publication/44707159_Connotative_Meaning_in_English_and_Italian_Colour-Word_Metaphors   Subscribe to Curiosity Daily from Curiosity.com to learn something new every day! You can also hear Discovery’s Cody Gough and Ashley Hamer as part of your Alexa Flash Briefing; Amazon smart speakers users, click/tap “enable” here: https://curiosity.im/podcast-flash-briefing

Episode Notes

Learn about how AI and Twitter could help you find the perfect job, and how the world is actually a greener place than it was 20 years ago. We’ll also answer a listener question about why we use the color “blue” to say we’re sad.

Job-Matching with Your Tweets by Kelsey Donk

Sources:

Earth Is Greener Than Before by Kelsey Donk

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Story 3 by Ashley Hamer (Listener question from Becky and Britni)

Sources:

Subscribe to Curiosity Daily from Curiosity.com to learn something new every day! You can also hear Discovery’s Cody Gough and Ashley Hamer as part of your Alexa Flash Briefing; Amazon smart speakers users, click/tap “enable” here: https://curiosity.im/podcast-flash-briefing

 

Find episode transcript here: https://curiosity-daily-4e53644e.simplecast.com/episodes/earth-is-greener-than-before-job-matching-with-your-tweets-and-why-blue-means-sad

Episode Transcription

CODY: Hi! You’re about to get smarter in just a few minutes with Curiosity Daily from curiosity-dot-com. I’m Cody Gough.

ASHLEY: And I’m Ashley Hamer. Today, you’ll learn about how AI and Twitter could help you find the perfect job, and how the world is actually a greener place than it was 20 years ago. We’ll also answer a listener question about why we use the color “blue” to say we’re sad.

CODY: Let’s satisfy some curiosity. 

KELSEY: AI may soon be able to analyze your tweets to match you to a job (Ashley)

We’ve known for a long time that work is more fulfilling when it matches up with your personalities, values, and interests. But now, researchers have figured out how to match people to the perfect jobs for their personality using — wait for it — Twitter. 

Okay, so this might sound like it’d be no more accurate than a Buzzfeed quiz, but hear me out. The trick comes down to pure data analysis. Using IBM Watson, an artificial intelligence engine, researchers analyzed tweets from more than 100,000 Twitter users with job titles in their bios. They took a look at how each person tweeted and scored them across 10 personality-related characteristics. They learned a lot! Like, users who were scientists often seem interested in new activities, think in symbols, and find repetition to be boring. But professional tennis players are more conscientious, organized, and agreeable. 

After linking that personality data to the users’ job titles, the researchers were able to make a “vocation compass map.” The map has twenty personality clusters with ideal jobs marked for each personality, and we’ll link to it in the show notes. That map showed that, no surprise, similar occupations tend to have similar personality types: a music agent, a radio station manager, and an event coordinator all fall into the same personality cluster, for example. But some clusters weren’t so predictable. The cluster that grouped computer programmer types also included geologists, cartographers, and grain farmers. I want to see THAT reality show.

The data itself is pretty cool, but the researchers didn’t stop there. They used that AI data to build a recommendation system — one that could find the best career fit for someone’s personality. The program they created could recommend a job matched to someone’s personality traits with an accuracy of more than 70 percent. Even when the system didn’t get a person’s ideal job exactly right, it came close. 

So, yes, your next career counselor could be a robot who swipes through your tweets to find the best possible job for you. It might sound weird, but it works!

KELSEY: The world is a greener place than it was 20 years ago (Cody)

The world is literally a greener place than it was 20 years ago, according to new NASA satellite data. In the age of the climate crisis, that might surprise you. Especially because NASA says the cause of the world’s greening comes from two of the world’s most quickly expanding countries. That’s right — China and India are responsible for our newly leafy Earth. 

In the mid-1990s, a group of Boston University scientists first noticed that the world was getting greener, but they didn’t know why. So, for twenty years, they tracked the planet’s green areas using an instrument called the Moderate Resolution Imaging Spectroradiometer, or MODIS. That instrument uses two satellites to view the entire Earth’s surface every one to two days. Since the year 2000, this pair of satellites has captured as many as four pictures of every single place on Earth, every day. Thanks to that data, we now know that Earth has gained more than two million square miles of additional green area per year, compared to the early 2000s. 

At first, the scientists thought the Earth’s greening must be due to the warming climate. Maybe the warm, wet air and extra carbon dioxide were turning northern forests leafy. But now the detailed satellite images show that a lot of the growth is actually coming from new programs in China aimed at conserving and expanding forests. The new green areas aren’t enough to offset the impact of lost tropical regions in Brazil and Indonesia, but they’re a start. 

And in both China and India, new farming practices have led to more food production and greener fields. Production of grains, vegetables, fruits, and other agricultural products has increased by as much as 40 percent since 2000 to feed the growing populations of these countries. 

The biggest takeaway scientists have found? When people realize there’s a problem, they seem to respond. The 70s and 80s weren’t great decades for biodiversity in India and China. But in the 90s when people realized there was a problem, they started to change course. Now, here we are. The Earth is greener thanks to humanity, and that should give us hope. 

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LISTENER Q: Why we use "blue" for "sad" (Ashley)

ASHLEY: Our story a couple weeks ago about why most people’s favorite color is blue led to the same fascinating question from two different listeners: Becky and Britni. Their questions boiled down to this: if blue’s so great, why do we associate it with sadness? 

The English language has associated “blue” with “sad” since at least the 14th century. That’s when Geoffrey Chaucer wrote this in his short poem “The Complaint of Mars” about lovers parting: “Wyth teres blewe, and with a wounded herte.” Basically, with blue tears and a wounded heart. Tears, might I remind you, are not blue, but these lovers are sad, so that’s the color Chaucer gave them. But why? One theory is that this connotation came out of “black and blue,” as in, having a bruise — perhaps on your heart? 

But the more you look at other languages, the more you realize that there’s no deep universal reason for why we associate “blue” with “sad.” Most languages don’t. German uses blue for drunk, Dutch uses it to mean “shy.” This becomes even more complicated when you learn that many languages have two different words for blue: Italian and Russian, for example, both have one word for dark blue and another for light blue. In fact, linguist Gill [Jill] Philip suggests that the reason the English word for the color of a clear sky is also associated with darkness and depression is because we just mashed the two shades together. At one point, the darker shade was more closely grouped with black and purple, so the sadness link made more sense. After all, Italian uses “nero,” or black, for sadness — not blue. But somewhere along the line, we dropped the word for light blue and just used the same word for all shades. So today, you can hear one song about blue skies and another about havin’ the blues, and the emotions they convey will be totally different. But the color is still the same. Thanks for your question, Becky and Britni! If you have a question, send it in to podcast at curiosity.com.

CODY: Before we recap what we learned today, here’s a sneak peek at what you’ll hear next week on Curiosity Daily.

ASHLEY: Next week, 

TOPICS

And more! Okay, so now, let’s recap what we learned today.

  1. Summary: Researchers used IBM's AI engine Watson to analyze tweets from 100,000+ Twitter users with job titles in their bios and gave each one a score across 10 personality-related characteristics based on the language in their tweets. With that, they were able to determine particular traits that were common in a given occupation. From the researchers' article on The Conversation: "...we found that different occupations tended to have very different personality profiles. For instance, software programmers and scientists were generally more open to experiencing a variety of new activities, were intellectually curious, tended to think in symbols and abstractions, and found repetition boring. On the other hand, elite tennis players tended to be more conscientious, organized and agreeable. Our findings point to the possibility of using data shared on social media to match an individual to a suitable job."
  2. Summary: The world is literally a greener place than it was 20 years ago, and data from NASA satellites has revealed a counterintuitive source for much of this new foliage: China and India. A new study shows that the two emerging countries with the world’s biggest populations are leading the increase in greening on land. The effect stems mainly from ambitious tree planting programs in China and intensive agriculture in both countries.

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CODY: Today’s stories were written by Ashley Hamer and Kelsey Donk, with scriptwriting and editing by Ashley Hamer, who’s the managing editor for Curiosity Daily.

ASHLEY: Additional scriptwriting by Cody Gough. Curiosity Daily is produced and edited by Cody Gough.

CODY: Have a great weekend, and join us again Monday to learn something new in just a few minutes.

ASHLEY: And until then, stay curious!