[BRIEF NOTE] On mapping the languages of the world and their networks

[rfmcdonald]

Language Log and Language Hat both linked to the paper "Links that speak: The global language network and its association with global fame". The abstract?

Languages vary enormously in global importance because of historical, demographic, political, and technological forces. However, beyond simple measures of population and economic power, there has been no rigorous quantitative way to define the global influence of languages. Here we use the structure of the networks connecting multilingual speakers and translated texts, as expressed in book translations, multiple language editions of Wikipedia, and Twitter, to provide a concept of language importance that goes beyond simple economic or demographic measures. We find that the structure of these three global language networks (GLNs) is centered on English as a global hub and around a handful of intermediate hub languages, which include Spanish, German, French, Russian, Portuguese, and Chinese. We validate the measure of a language’s centrality in the three GLNs by showing that it exhibits a strong correlation with two independent measures of the number of famous people born in the countries associated with that language. These results suggest that the position of a language in the GLN contributes to the visibility of its speakers and the global popularity of the cultural content they produce.

Sciencemag's Michael Erard goes into more detail.

[Shahar] Ronen and co-authors from MIT, Harvard University, Northeastern University, and Aix-Marseille University tackled the problem by describing three global language networks based on bilingual tweeters, book translations, and multilingual Wikipedia edits. The book translation network maps how many books are translated into other languages. For example, the Hebrew book, translated from Hebrew into English and German, would be represented in lines pointing from a node of Hebrew to nodes of English and German. That network is based on 2.2 million translations of printed books published in more than 1000 languages. As in all of the networks, the thickness of the lines represents the number of connections between nodes. For tweets, the researchers used 550 million tweets by 17 million users in 73 languages. In that network, if a user tweets in, say, Hindi as well as in English, the two languages are connected. To build the Wikipedia network, the researchers tracked edits in up to five languages done by editors, carefully excluding bots.

In all three networks, English has the most transmissions to and from other languages and is the most central hub, the team reports online today in the Proceedings of the National Academy of Sciences. But the maps also reveal “a halo of intermediate hubs,” according to the paper, such as French, German, and Russian, which serve the same function at a different scale.

In contrast, some languages with large populations of speakers, such as Mandarin, Hindi, and Arabic, are relatively isolated in these networks. This means that fewer communications in those languages reach speakers of other languages. Meanwhile, a language like Dutch—spoken by 27 million people—can be a disproportionately large conduit, compared with a language like Arabic, which has a whopping 530 million native and second-language speakers. This is because the Dutch are very multilingual and very online.

The network maps show what is already widely known: If you want to get your ideas out, you can reach a lot of people through the English language. But the maps also show how speakers in disparate languages benefit from being indirectly linked through hub languages large and small. On Twitter, for example, ideas in Filipino can theoretically move to the Korean-speaking sphere through Malay, whereas the most likely path for ideas to go from Turkish to Malayalam (spoken in India by 35 million people) is through English. These networks are revealed in detail at the study’s website.

The networks exposed, connecting Russian to a variety of Eurasian languages for instance or English to South Asian languages, are quite revealing. Fascinating stuff.