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Vespignani, Alessandro

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Vespignani

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Alessandro

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Vespignani, Alessandro
Author's Publications: search.filters.isAuthorOfPublication.3a745b05-c07f-4256-928d-ed4748afd455

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    Links that speak: The global language network and its association with global fame
    (Proceedings of the National Academy of Sciences, 2014) Ronen, Shahar; Gonçalves, Bruno; Hu, Kevin Z.; Vespignani, Alessandro; Pinker, Steven; Hidalgo, César A.
    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.
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    Digital Epidemiology
    (Public Library of Science, 2012) Salathé, Marcel; Bengtsson, Linus; Bodnar, Todd J.; Brewer, Devon D.; Brownstein, John; Buckee, Caroline; Campbell, Ellsworth M.; Cattuto, Ciro; Khandelwal, Shashank; Mabry, Patricia L.; Vespignani, Alessandro
    Mobile, social, real-time: the ongoing revolution in the way people communicate has given rise to a new kind of epidemiology. Digital data sources, when harnessed appropriately, can provide local and timely information about disease and health dynamics in populations around the world. The rapid, unprecedented increase in the availability of relevant data from various digital sources creates considerable technical and computational challenges.