Mediaboss Marketing

PUBLIC RELEASE DATE:

16-Dec-2014

Contact: Abby Abazorius abbya@mit.edu 617-253-2709 Massachusetts Institute of Technology @MIT

By analyzing data on multilingual Twitter users and Wikipedia editors and on 30 years' worth of book translations in 150 countries, researchers at MIT, Harvard University, Northeastern University, and Aix Marseille University have developed network maps that they say represent the strength of the cultural connections between speakers of different languages.

This week, in the Proceedings of the National Academy of Sciences, they show that a language's centrality in their network -- as defined by both the number and the strength of its connections -- better predicts the global fame of its speakers than either the population or the wealth of the countries in which it is spoken.

"The network of languages that are being translated is an aggregation of the social network of the planet," says Cesar Hidalgo, the Asahi Broadcasting Corporation Career Development Assistant Professor of Media Arts and Sciences and senior author on the paper. "Not everybody shares a language with everyone else, and therefore 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. That gives them a disproportionate power and responsibility. On the one hand, they have a much easier time disseminating the content that they produce. On the other hand, as information flows through people, it gets colored by the ideas and the biases that those people have."

Plotting polyglots

Hidalgo and his students Shahar Ronen -- first author on the new paper -- and Kevin Hu, together with Harvard's Steven Pinker, Bruno Goncalves of Aix Marseille University, and Alessandro Vespignani of Northeastern, included a given Twitter user in their data set if he or she had at least three sentence-long tweets in a language other than his or her primary language. That left them with 17 million of Twitter's roughly 280 million users. They had similar thresholds for Wikipedia users who had edited entries in more than one language, which gave them a data set of 2.2 million Wikipedia editors.

In both cases, the strength of the connection between any two languages was determined by the number of users who had demonstrated facility with both of them.

The translation data came from UNESCO's Index Translationum, which catalogues 2.2 million book translations, in more than 1,000 languages, published between 1979 and 2011. There, the strength of the connection between two languages was determined by the number of translations between them.

Read more:
How information moves between cultures