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The Twitter of Babel: Mapping World Languages through Microblogging Platforms

Author

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  • Delia Mocanu
  • Andrea Baronchelli
  • Nicola Perra
  • Bruno Gonçalves
  • Qian Zhang
  • Alessandro Vespignani

Abstract

Large scale analysis and statistics of socio-technical systems that just a few short years ago would have required the use of consistent economic and human resources can nowadays be conveniently performed by mining the enormous amount of digital data produced by human activities. Although a characterization of several aspects of our societies is emerging from the data revolution, a number of questions concerning the reliability and the biases inherent to the big data “proxies” of social life are still open. Here, we survey worldwide linguistic indicators and trends through the analysis of a large-scale dataset of microblogging posts. We show that available data allow for the study of language geography at scales ranging from country-level aggregation to specific city neighborhoods. The high resolution and coverage of the data allows us to investigate different indicators such as the linguistic homogeneity of different countries, the touristic seasonal patterns within countries and the geographical distribution of different languages in multilingual regions. This work highlights the potential of geolocalized studies of open data sources to improve current analysis and develop indicators for major social phenomena in specific communities.

Suggested Citation

  • Delia Mocanu & Andrea Baronchelli & Nicola Perra & Bruno Gonçalves & Qian Zhang & Alessandro Vespignani, 2013. "The Twitter of Babel: Mapping World Languages through Microblogging Platforms," PLOS ONE, Public Library of Science, vol. 8(4), pages 1-9, April.
    • Handle: RePEc:plo:pone00:0061981
    DOI: 10.1371/journal.pone.0061981
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    1. Maxime Lenormand & Antònia Tugores & Pere Colet & José J Ramasco, 2014. "Tweets on the Road," PLOS ONE, Public Library of Science, vol. 9(8), pages 1-12, August.
    2. Shota Saito & Yoshito Hirata & Kazutoshi Sasahara & Hideyuki Suzuki, 2015. "Tracking Time Evolution of Collective Attention Clusters in Twitter: Time Evolving Nonnegative Matrix Factorisation," PLOS ONE, Public Library of Science, vol. 10(9), pages 1-17, September.
    3. Wright, Nataliya Langburd & Nagle, Frank & Greenstein, Shane, 2023. "Open source software and global entrepreneurship," Research Policy, Elsevier, vol. 52(9).
    4. Milena Lopreite & Michelangelo Puliga & Massimo Riccaboni, 2018. "The Global Health Networks: A Comparative Analysis of Tuberculosis, Malaria and Pneumonia Using Social Media Data," Working Papers 01/2018, IMT School for Advanced Studies Lucca, revised Jan 2018.
    5. Fabio Lamanna & Maxime Lenormand & María Henar Salas-Olmedo & Gustavo Romanillos & Bruno Gonçalves & José J Ramasco, 2018. "Immigrant community integration in world cities," PLOS ONE, Public Library of Science, vol. 13(3), pages 1-19, March.
    6. Maxime Lenormand & Miguel Picornell & Oliva G Cantú-Ros & Antònia Tugores & Thomas Louail & Ricardo Herranz & Marc Barthelemy & Enrique Frías-Martínez & José J Ramasco, 2014. "Cross-Checking Different Sources of Mobility Information," PLOS ONE, Public Library of Science, vol. 9(8), pages 1-10, August.
    7. B. Sofia Gil-Clavel & André Grow & Maarten J. Bijlsma, 2022. "Analyzing EU-15 immigrants’ language acquisition using Twitter data," MPIDR Working Papers WP-2022-012, Max Planck Institute for Demographic Research, Rostock, Germany.
    8. Letchford, Adrian & Preis, Tobias & Moat, Helen Susannah, 2016. "The advantage of simple paper abstracts," Journal of Informetrics, Elsevier, vol. 10(1), pages 1-8.
    9. Borondo, J. & Morales, A.J. & Benito, R.M. & Losada, J.C., 2014. "Mapping the online communication patterns of political conversations," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 414(C), pages 403-413.
    10. Daniele Barchiesi & Helen Susannah Moat & Christian Alis & Steven Bishop & Tobias Preis, 2015. "Quantifying International Travel Flows Using Flickr," PLOS ONE, Public Library of Science, vol. 10(7), pages 1-8, July.
    11. Kristoufek, Ladislav, 2015. "Power-law correlations in finance-related Google searches, and their cross-correlations with volatility and traded volume: Evidence from the Dow Jones Industrial components," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 428(C), pages 194-205.
    12. Erick Elejalde & Leo Ferres & Eelco Herder, 2018. "On the nature of real and perceived bias in the mainstream media," PLOS ONE, Public Library of Science, vol. 13(3), pages 1-28, March.
    13. Minda Hu & Mayank Kejriwal, 2022. "Measuring spatio-textual affinities in twitter between two urban metropolises," Journal of Computational Social Science, Springer, vol. 5(1), pages 227-252, May.
    14. David Flores-Ruiz & Adolfo Elizondo-Salto & María de la O. Barroso-González, 2021. "Using Social Media in Tourist Sentiment Analysis: A Case Study of Andalusia during the Covid-19 Pandemic," Sustainability, MDPI, vol. 13(7), pages 1-19, March.
    15. Saba Resnik & Mateja Kos Koklič, 2018. "User-Generated Tweets about Global Green Brands: A Sentiment Analysis Approach," Tržište/Market, Faculty of Economics and Business, University of Zagreb, vol. 30(2), pages 125-145.

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