Twitter language mapThe number of famous people a country produces has less to do with its wealth or the size of its population and more to do with its language, according to a recent study by the Massachusetts Institute of Technology.

It's likely not surprising that English is the most globally influential language, but when MIT researchers mapped how information flows around the world, it became evident that some of the most widely spoken languages aren't as influential as other lesser-spoken ones.

For example, with nearly 2 billion speakers, Mandarin is the most spoken language in the world, but if you're a native English speaker looking to spread your message, you're better off learning Spanish.

Why? It boils down to how information written in English is shared in other languages.

As the graphic on the right illustrates, most tweets are translated into or from English even though the Chinese are Twitter's most active users.

This graphic is a visual representations of Twitter's global language network, and it was created as part of a study inspired by former MIT student Shahar Ronen's master's thesis. A bilingual Hebrew-English speaker, Ronen told his adviser, César Hidalgo, about a Hebrew book that hadn't been translated into English.

"I was able to bridge a certain culture gap because I was multilingual," he told Science Magazine.

That book got Ronen and Hidalgo thinking about how multilingual people transmit information, so they set out to map global language networks across various mediums.

They compiled data from three sources: 382 million Wikipedia edits, 550 million tweets from multilingual users, and 2.2 million translations of printed books published in more than 1,000 languages.

To measure the significance of a language within each of these mediums, researchers used what's called eigenvector centrality, which is calculated by assessing how well connected an individual is to the parts of a network with the greatest connectivity.

They mapped a global language network for each of the three data sets and found that each showed English as its most central hub, along with a few intermediate hub languages like Spanish, German and French.

While languages like Mandarin and Arabic are spoken by millions, they're more isolated in the networks because there are fewer translations between them and the hub languages.

Wikipedia language mapHowever, a language like Dutch — which is spoken by just over 20 million people — has more influence than Arabic because Dutch speakers tend to be multilingual and active online.

There are differences among the networks though. For example, the maps of Twitter and Wikipedia reveal a larger share of languages associated with developing countries, such as Filipino and Swahili, compared with written books. This suggests that online forms of communication are more inclusive.

It makes sense that languages with more connections would lead to more information in those languages being widely disseminated, but researchers went a step further to see if being born into that language correlated with fame.

They compiled a list of famous people using the book "Human Accomplishment" and MIT’s Pantheon, a project that maps cultural production, and confirmed that speaking a hub language increased the likelihood of achieving fame.

However, the maps tell us more than simply "You can reach more people by speaking English." They also illustrate how languages that may not be as widely spoken can benefit from being linked to a hub language.

For example, ideas in Filipino can easily move to Korean speakers via Malay, the national language of Malaysia, Indonesia and Brunei.

Still, the researchers note that their maps don't reflect most of the world's population because the data they pulled from is the creation of "elites," literate people with an online presence.

"The elites of global languages have a disproportionate amount of power and responsibility because they are tacitly shaping the way in which distant cultures see each other — even if this is not their goal," their paper reads.

Below, take a look at the global language network created from translations of printed books. You can view the Twitter and Wikipedia maps in the authors' paper in the Proceedings of the National Academy of Sciences.

language influence map

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