By analyzing data on book translations and multilingual Twitter users and Wikipedia editors, researchers at MIT, Harvard, Northeastern, and Aix Marseille University have developed network maps that they say represent the strength of the cultural connections between speakers of different languages.

In a paper in the Proceedings of the National Academy of Sciences, they showed that a language’s centrality in their network better predicts the global fame of its speakers than either the population or the wealth of the countries in which it is spoken.

“The global social network is structured through these circuitous paths in which people in some language groups are by definition way more central than others,” says Cesar Hidalgo, assistant professor of media arts and sciences and senior author on the paper. “That gives them a disproportionate power and responsibility.”

In two of the network maps, the strength of the connections between any two languages depended on the number of Twitter users or Wikipedia editors who had demonstrated facility in both of them. The third map was based on UNESCO’s Index Translationum, which catalogues 2.2 million book translations in more than 1,000 languages.

To measure global fame, the researchers identified people with Wikipedia entries in at least 26 languages. They also looked at the 4,002 people profiled in the American political scientist Charles ­Murray’s book Human Accomplishment. In both cases, at least one of the language centrality networks provided a better correlation to fame than the number of speakers of a language and the GDPs of the countries in which it is spoken.