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The Twitter of Babel: Mapping World Languages through Microblogging Platforms
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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.
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“By mapping the use of languages across countries, Mocanu et al. (2013) observed seasonal variations in the linguistic composition of each country, as well as between geographical areas at different granularity scales, even at the level of city neighborhoods.”
From Social Data: Biases, Methodological Pitfalls, and Ethical Boundaries (2019) · cites this paper as Mocanu et al., 2013
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Citations
Cites
Understanding individual human mobility patterns
González, M. C., Hidalgo, C. A., & Barabási, A.-Ĺ. (2008) · Nature · doi:10.1038/nature06958 · Cited by 6,186
Predicting Elections with Twitter: What 140 Characters Reveal about Political Sentiment
Tumasjan, A., Sprenger, T. O., Sandner, P., & Welpe, I. M. (2010) · Proceedings of the International AAAI Conference on Web and Social Media · doi:10.1609/icwsm.v4i1.14009 · Cited by 2,647
Structure and tie strengths in mobile communication networks
Onnela, J.-P. “., Saramäki, J., Hyvönen, J., Szabó, G., Lazer, D., Kaski, K. K., Kertész, J., & Barabási, A.-Ĺ. (2007) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0610245104 · Cited by 1,945
Talking about tactile experiences
Obrist, M., Seah, S. A., & Subramanian, S. (2013) · CHI Conference on Human Factors in Computing Systems · doi:10.1145/2470654.2466220 · Cited by 1,634
Understanding the Demographics of Twitter Users
Mislove, A. E., Lehmann, S., Ahn, Y., Onnela, J.-P. “., & Rosenquist, J. (2021) · Proceedings of the International AAAI Conference on Web and Social Media · doi:10.1609/icwsm.v5i1.14168 · Cited by 761
Modeling Users' Activity on Twitter Networks: Validation of Dunbar's Number
Gonçalves, B., Perra, N., & Vespignani, A. (2011) · PLoS ONE · doi:10.1371/journal.pone.0022656 · Cited by 638
Self-citationTowards detecting influenza epidemics by analyzing Twitter messages
Culotta, A. (2010) · doi:10.1145/1964858.1964874 · Cited by 631
Takhteyev, Y., Gruzd, A. A., & Wellman, B. (2011) · Social Networks · doi:10.1016/j.socnet.2011.05.006 · Cited by 617
Predicting the Political Alignment of Twitter Users
Conover, M. D., Goncalves, B., Ratkiewicz, J., Flammini, A., & Menczer, F. (2011) · 2011 IEEE Third Int'l Conference on Privacy, Security, Risk and Trust and 2011 IEEE Third Int'l Conference on Social Computing · doi:10.1109/passat/socialcom.2011.34 · Cited by 588
Self-citationRatkiewicz (2011) · doi:10.1145/1963192.1963301 · Cited by 541
Self-citation
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- Mislove A, Lehmann S, Ahn YY, Onnela JP, Rosenquist JN (2011) Understanding the demographics of twitter users. In: In Proceedings of the Fifth International AAAI Conference on Weblogs and Social Media.
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Items 201–294 of 294
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Hultquist, C. (2020) · International Journal of Humanities and Arts Computing · doi:10.3366/ijhac.2020.0253 · Cited by 3
Tyrkkö, J., Levin, M., & Laitinen, M. (2021) · World Englishes · doi:10.1111/weng.12545 · Cited by 3
Measuring spatio-textual affinities in twitter between two urban metropolises
Hu, M., & Kejriwal, M. (2021) · Journal of Computational Social Science · doi:10.1007/s42001-021-00129-5 · Cited by 3
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Kellert, O. (2024) · Revue Romane Langue et littérature International Journal of Romance Languages and Literatures · doi:10.1075/rro.23006.kel · Cited by 2
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Zhu, Z., Chen, H., Shi, Y., Zhang, M., Sun, C., Cheng, X., & Jin, J. (2026) · Chinese Political Science Review · doi:10.1007/s41111-025-00330-1 · Cited by 2
Jenkins, M. (2020) · Rhetoric, politics and society · doi:10.1007/978-3-030-36525-7_4 · Cited by 2
Schünemann, W. J., Steiger, S., & Stier, S. (2016) · Springer eBooks · doi:10.1007/978-3-658-13500-3_10 · Cited by 2
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Kellert, O. (2023) · De Gruyter eBooks · doi:10.1515/9783110746082-007 · Cited by 2
Gil‐Clavel, S., & Mulder, C. H. (2024) · Population Research and Policy Review · doi:10.1007/s11113-024-09891-6 · Cited by 2
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Ferrara, E., Catanese, S., & Fiumara, G. (2015) · Springer eBooks · doi:10.1007/978-3-319-14011-7_10 · Cited by 2
Portales, J. C., & Alcaino, J. A. C. (2019) · Comhumanitas · doi:10.31207/rch.v9i2.166 · Cited by 2
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Elasmar, M. G., Wu, H. D., & Groshek, J. (2024) · International Political Science Review · doi:10.1177/01925121241228556 · Cited by 2
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The structure and implications of the global language network
Ronen, S. (2013) · Cited by 2
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Limiti e possibilità degli online social data
Giglietto, F., & Rossi, L. (2015) · SOCIOLOGIA DELLA COMUNICAZIONE · doi:10.3280/sc2015-049002 · Cited by 1
Existence of outsiders as a characteristic of online communication networks
Takaguchi, T., Maehara, T., Kawarabayashi, K., & Toyoda, M. (2018) · Network Science · doi:10.1017/nws.2018.17 · Cited by 1
A Language-Centric Study of Twitter Connectivity
Saha, P., & de Menezes, R. P. (2016) · Lecture notes in computer science · doi:10.1007/978-3-319-47874-6_33 · Cited by 1
Fowler, J. H., Mocanu, D., STEINERT-THRELKELD, Z., & Vespignani, A. (2014) · Cited by 1
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McPherson, E., & Probert, T. (2017) · Brill | Nijhoff eBooks · doi:10.1163/9789004304703_011 · Cited by 1
Diffusion of Twitter Messages on Dallas Mass Shooting: Patterns and Factors
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BORDERS OF IDENTITY AND ACTUAL LANGUAGE USE IN UKRAINE: AN ANALYSIS OF GEOTAGGED TWEETS
Pavliy, B., & Lewis, J. (2015) · Japanese Slavic and East European Studies · doi:10.5823/jsees.36.0_77 · Cited by 1
Girginova, K. (2020) · International journal of communication · Cited by 1
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Nordenson, J. (2016) · CyberOrient · doi:10.1002/j.cyo2.20161001.0006 · Cited by 1
Tweeted Attitudes towards Women Parliamentary Candidates in Kuwait: A Social Dominance Perspective
Mesbah, H. (2021) · Journal of Digital Social Research · doi:10.33621/jdsr.v4i1.114 · Cited by 1
Orosa, B. G., & García, X. L. (1970) · Communication & Society · doi:10.15581/003.32.37818 · Cited by 1
Robinson, J. Y. (2022) · Health & New Media Research · doi:10.22720/hnmr.2022.6.2.189 · Cited by 1
Language Detection for Global Communication
Karmakar, A., Basu, S., Roy, P. S., Das, S., & Ghosh, T. (2024) · Lecture notes in networks and systems · doi:10.1007/978-981-97-8090-7_35 · Cited by 1
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Martins, T., & Azevedo, I. (2015) · Iberian Conference on Information Systems and Technologies (CISTI) · doi:10.1109/cisti.2015.7170478 · Cited by 1
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Coats, S. (2016) · Cited by 1
El acceso a la literatura de revistas españolas de Ciencias de la Salud a través de IBECS y ScIELO
Sánchez, A. F. G. (2017) · Metas de Enfermería · doi:10.35667/metasenf.2019.20.1003081020 · Cited by 1
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Anttila, T. (2018) · Cited by 1
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Flyverbom, M., Madsen, A. K., & Rasche, A. (2016) · Cited by 1
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Novaes, M. F. T. D. A. (2020) · U Porto Journal of Engineering · doi:10.24840/2183-6493_006.001_0005 · Cited by 1
George Floyd and cosmopolitan memory formation in online networks: A report from Northern Europe
Robinson, J. Y. (2022) · Revista Mediterránea de Comunicación · doi:10.14198/medcom.21834 · Cited by 2
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Gonçalves, B., & Sánchez, D. (2015) · arXiv (Cornell University) · Cited by 1
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Elejalde, E., Ferres, L., & Schifanella, R. (2018) · arXiv (Cornell University) · doi:10.15488/5073 · Cited by 1
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Starnini, M. (2014) · UPCommons institutional repository (Universitat Politècnica de Catalunya) · doi:10.5821/dissertation-2117-95523 · Cited by 2
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Téllez, E. S., Moctezuma, D., Miranda‐Jiménez, S., & Graff, M. (2021) · arXiv (Cornell University) · Cited by 1
Lin, B., Zou, L., Duffield, N. G., Mostafavi, A., Cai, H., Zhou, B., Tao, J., Yang, M., Mandal, D., & Abedin, J. (2021) · arXiv (Cornell University) · doi:10.48550/arxiv.2111.03446 · Cited by 1
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Miguel, M. S., & Toral, R. (2025) · Elsevier eBooks · doi:10.1016/b978-0-323-95504-1.00792-4 · Cited by 1
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Heinsalu, E., Patriarca, M., & Sanchez, D. (2025) · Elsevier eBooks · doi:10.1016/b978-0-323-95504-1.00991-1 · Cited by 1
Active control of complexity growth in Language Games
Schueller, W. (2018) · theses.fr (ABES) · doi:10.70675/87b2cc34z8b22z4bf6z8db0zf07d6b1f8a89 · Cited by 1
Data science and spatio-temporal resolved social networks
Mocanu, D. (2014) · Digital Repository Service (Northeastern University) · doi:10.17760/d20005098
Self-citatione-Science for Digital Development: ICT4ICT4D
Hilbert, M. (2015) · eScholarship (California Digital Library)
Language Relations on Twitter: A Network Science Approach
Saha, P. (2017)
Palomares, J. C. G., Salas-Olmedo, M. H., Moya‐Gómez, B., Condeço-Melhorado, A. M., & Gutierrrez, J. (2017) · arXiv (Cornell University) · doi:10.48550/arxiv.1705.07956
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Shihab, S. (2017) · Digital Commons - University of South Florida (University of South Florida)
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Pacheco, D. F., Saha, P., Neto, F. B. D. L., & de Menezes, R. P. (2017) · IEEE SmartWorld, Ubiquitous Intelligence & Computing, Advanced & Trusted Computing, Scalable Computing & Communications, Cloud & Big Data Computing, Internet of People and Smart City Innovation (SmartWorld/SCALCOM/UIC/ATC/CBDCom/IOP/SCI) · doi:10.1109/uic-atc.2017.8397543
Software for monitoring current trends on Twitter
Kapantai, E. (2018)
A computational investigation of the propaganda model
Elejalde, E. (2019) · ACM SIGWEB Newsletter · doi:10.1145/3293874.3293877
Quantifying & characterizing information diets of social media users
Kulshrestha, J. (2018) · Publications of the UdS (Saarland University) · doi:10.22028/d291-27621
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Salas-Olmedo, M. H., Palomares, J. C. G., & Puebla, J. G. (2017) · arXiv (Cornell University) · doi:10.48550/arxiv.1705.07951
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Abdollahi, S. (2020) · TIB AV-Portal · doi:10.5446/50457
Biswas, M. R. (2021) · arXiv (Cornell University) · doi:10.48550/arxiv.2103.11385
Jenkins, M. (2021) · Asian Journal of Comparative Politics · doi:10.1177/20578911211000854
Spruce, M. C. (2021) · Natural hazards and earth system sciences · doi:10.5194/nhess-2020-413-ac2
Contagion and ranking processes in complex networks
Zhang, Q. (2014) · Digital Repository Service (Northeastern University) · doi:10.17760/d20005064
Self-citation(2021) · Natural hazards and earth system sciences · doi:10.5194/nhess-2020-413-rc2
Spruce, M. (2021) · Natural hazards and earth system sciences · doi:10.5194/nhess-2020-413-ac1
Analyzing EU-15 immigrants’ language acquisition using Twitter data
Gil-Clavel, B. S., Grow, A., & Bijlsma, M. J. (2022) · doi:10.4054/mpidr-wp-2022-012
(2023) · The MIT Press eBooks · doi:10.7551/mitpress/13999.003.0013
Studying Social Interactions Using Digital Trace Data
Gil‐Clavel, S. (2023) · doi:10.33612/diss.688253059
Spanish language trend on Twitter: an analysis of modern writing
Torres, C. G. L., Macías, J. V., & González, B. A. R. (2024) · ECORFAN Journal Bolivia · doi:10.35429/ejb.2024.20.11.17.27
Population Distribution and Migration Patterns
Moghaddam, S. N. M., & Cao, H. (2024) · City development · doi:10.1007/978-981-97-5116-7_4
Fiallos, A. (2024) · International Conference on eDemocracy & eGovernment · doi:10.1109/icedeg61611.2024.10702079
Zhang, Y., & Fang, Z. (2025) · Journal of the Association for Information Science and Technology · doi:10.1002/asi.70002
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Capkin, S. O. K., Persia, L., Usami, D. S., Krishnamurthy, T. S., & González-Hernández, B. (2025) · Transportation research procedia · doi:10.1016/j.trpro.2025.06.059
Farquharson, J. I. (2025) · Communications Earth & Environment · doi:10.1038/s43247-025-02757-5
175Diffusion across the grammar
Dunn, J. (2026) · De Gruyter eBooks · doi:10.1515/9783111615806-008
Pogrebna, G., & Hills, T. T. (2026) · Cambridge University Press eBooks · doi:10.1017/9781108939010.035
Understanding Collective Behaviour Using Online Data and Mobile Phones
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Duplaix, J., Abad, S., Bruna, M., Legout, A., Nommer, A., Nourrit-Lucas, D., & Ninot, G. (2026) · Journal of Medical Internet Research · doi:10.2196/97760
Time Series Analysis of Online Social Media
Artime, O. (2014)
Metadata
- Authors
- Mocanu, D., Baronchelli, A., Perra, N., Gonçalves, B., Zhang, Q., & Vespignani, A.
- Affiliations
- Northeastern University (US)
- Centre National de la Recherche Scientifique (FR)
- Corresponding author
- Vespignani, Alessandro
- Venue
- PLoS ONE
- Publisher
- Public Library of Science (PLoS)
- Published
- 2013-04-18
- Volume
- 8
- Issue
- 4
- Pages
- e61981
- ISSN
- 1932-6203 (ISSN-L)
- PMC
- PMC3630228
- OpenAlex
- W2044734026
- Cited by
- 293
- References
- 30
- Citations by year
- 2026: 5 · 2025: 8 · 2024: 10 · 2023: 13 · 2022: 16 · 2021: 21 · 2020: 17 · 2019: 26 · 2018: 31 · 2017: 38 · 2016: 38 · 2015: 36 · 2014: 23 · 2013: 10
- FWCI
- 151.78
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Locations
- PLoS ONE (publishedVersion, cc-by)
- Europe PMC (PubMed Central) (publishedVersion, other-oa)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- Greenwich Academic Literature Archive (University of Greenwich) (acceptedVersion)
- City Research Online (City University London) (acceptedVersion)
- arXiv (Cornell University) (submittedVersion)
- HAL (submittedVersion, cc-by)
- RePEc: Research Papers in Economics (submittedVersion)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- arXiv (Cornell University)
- Funders
- National Science Foundation (1101743)
- Intelligence Advanced Research Projects Activity (D12PC00285)
- Topics
- Social Sciences › Linguistics and Language › Linguistic and Sociocultural Studies
- Social Sciences › Transportation › Human Mobility and Location-Based Analysis
- Social Sciences › Arts and Humanities › Literature and Literary Theory › Digital Humanities and Scholarship
- Keywords
- dialect geography, microblogging, Twitter, multilingual regions, linguistic homogeneity, language use patterns
- MeSH terms
- Humans, Language, Linguistics, Internet, Blogging, Data Mining, Social Media
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