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      The Twitter of Babel: Mapping World Languages through Microblogging Platforms

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          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.

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          Most cited references14

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          Understanding individual human mobility patterns

          Despite their importance for urban planning, traffic forecasting, and the spread of biological and mobile viruses, our understanding of the basic laws governing human motion remains limited thanks to the lack of tools to monitor the time resolved location of individuals. Here we study the trajectory of 100,000 anonymized mobile phone users whose position is tracked for a six month period. We find that in contrast with the random trajectories predicted by the prevailing Levy flight and random walk models, human trajectories show a high degree of temporal and spatial regularity, each individual being characterized by a time independent characteristic length scale and a significant probability to return to a few highly frequented locations. After correcting for differences in travel distances and the inherent anisotropy of each trajectory, the individual travel patterns collapse into a single spatial probability distribution, indicating that despite the diversity of their travel history, humans follow simple reproducible patterns. This inherent similarity in travel patterns could impact all phenomena driven by human mobility, from epidemic prevention to emergency response, urban planning and agent based modeling.
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            Modeling Users' Activity on Twitter Networks: Validation of Dunbar's Number

            Microblogging and mobile devices appear to augment human social capabilities, which raises the question whether they remove cognitive or biological constraints on human communication. In this paper we analyze a dataset of Twitter conversations collected across six months involving 1.7 million individuals and test the theoretical cognitive limit on the number of stable social relationships known as Dunbar's number. We find that the data are in agreement with Dunbar's result; users can entertain a maximum of 100–200 stable relationships. Thus, the ‘economy of attention’ is limited in the online world by cognitive and biological constraints as predicted by Dunbar's theory. We propose a simple model for users' behavior that includes finite priority queuing and time resources that reproduces the observed social behavior.
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              Geography of Twitter networks

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                Author and article information

                Contributors
                Role: Editor
                Journal
                PLoS One
                PLoS ONE
                plos
                plosone
                PLoS ONE
                Public Library of Science (San Francisco, USA )
                1932-6203
                2013
                18 April 2013
                : 8
                : 4
                : e61981
                Affiliations
                [1 ]Laboratory for the Modeling of Biological and Socio-technical Systems, Northeastern University, Boston, Massachusetts, United States of America
                [2 ]Aix Marseille Université, CNRS, CPT, UMR 7332, Marseille, France
                [3 ]Institute for Quantitative Social Sciences at Harvard University, Cambridge, Massachusetts, United States of America
                [4 ]Institute for Scientific Interchange Foundation, Turin, Italy
                University of Zaragoza, Spain
                Author notes

                Competing Interests: The authors have declared that no competing interests exist.

                Conceived and designed the experiments: DM AB NP BG AV. Performed the experiments: DM. Analyzed the data: DM AB NP BG AV. Contributed reagents/materials/analysis tools: DM AB NP BG QZ AV. Wrote the paper: DM AB NP BG AV.

                Article
                PONE-D-13-01420
                10.1371/journal.pone.0061981
                3630228
                23637940
                bf906e45-515c-479b-9223-fe893147c87a
                Copyright @ 2013

                This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

                History
                : 5 January 2013
                : 18 March 2013
                Page count
                Pages: 9
                Funding
                The authors acknowledge the support by the National Science Foundation ICES award CCF-1101743. For the analysis of data data outside of the United States of America the authors acknowledge the Intelligence Advanced Research Projects Activity (IARPA) via Department of Interior National Business Center (DoI/NBC) contract number D12PC00285. The views and conclusions contained herein are those of the authors and should not be interpreted as necessarily representing the official policies or endorsements, either expressed or implied, of IARPA, DoI/NBE, or the United States Government. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
                Categories
                Research Article
                Computer Science
                Information Technology
                Engineering
                Signal Processing
                Data Mining
                Mathematics
                Applied Mathematics
                Complex Systems
                Social and Behavioral Sciences
                Communications
                Natural Language
                Geography
                Human Geography
                Behavioral Geography
                Linguistics
                Linguistic Geography
                Sociology
                Social Networks

                Uncategorized
                Uncategorized

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