Inferring international and internal migration patterns from twitter data

Emilio Zagheni, Venkata Rama Kiran Garimella, Ingmar Weber, Bogdan State

Research output: Chapter in Book/Report/Conference proceedingConference contribution

55 Citations (Scopus)

Abstract

Data about migration flows are largely inconsistent across countries, typically outdated, and often inexistent. Despite the importance of migration as a driver of demographic change, there is limited availability of migration statistics. Generally, researchers rely on census data to indirectly estimate flows. However, little can be inferred for specific years between censuses and for recent trends. The increasing availability of geolocated data from online sources has opened up new opportunities to track recent trends in migration patterns and to improve our understanding of the relationships between internal and international migration. In this paper, we use geolocated data for about 500,000 users of the social network website "Twitter". The data are for users in OECD countries during the period May 2011- April 2013. We evaluated, for the subsample of users who have posted geolocated tweets regularly, the geographic movements within and between countries for independent periods of four months, respectively. Since Twitter users are not representative of the OECD population, we cannot infer migration rates at a single point in time. However, we proposed a difference-indifferences approach to reduce selection bias when we infer trends in out-migration rates for single countries. Our results indicate that our approach is relevant to address two longstanding questions in the migration literature. First, our methods can be used to predict turning points in migration trends, which are particularly relevant for migration forecasting. Second, geolocated Twitter data can substantially improve our understanding of the relationships between internal and international migration. Our analysis relies uniquely on publicly available data that could be potentially available in real time and that could be used to monitor migration trends. The Web Science community is well-positioned to address, in future work, a number of methodological and substantive questions that we discuss in this article. ?Emilio Zagheni worked on this article while he was a visiting researcher at the Wittgenstein Centre (IIASA, VID/ÖAW, WU), where he received helpful comments on this paper. In particular, we would like to thank Guy Abel and Nikola Sander.

Original languageEnglish
Title of host publicationWWW 2014 Companion - Proceedings of the 23rd International Conference on World Wide Web
PublisherAssociation for Computing Machinery, Inc
Pages439-444
Number of pages6
ISBN (Electronic)9781450327459
DOIs
Publication statusPublished - 7 Apr 2014
Event23rd International Conference on World Wide Web, WWW 2014 - Seoul, Korea, Republic of
Duration: 7 Apr 201411 Apr 2014

Other

Other23rd International Conference on World Wide Web, WWW 2014
CountryKorea, Republic of
CitySeoul
Period7/4/1411/4/14

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Keywords

  • Migration
  • Selection bias
  • Twitter

ASJC Scopus subject areas

  • Computer Networks and Communications
  • Software

Cite this

Zagheni, E., Garimella, V. R. K., Weber, I., & State, B. (2014). Inferring international and internal migration patterns from twitter data. In WWW 2014 Companion - Proceedings of the 23rd International Conference on World Wide Web (pp. 439-444). Association for Computing Machinery, Inc. https://doi.org/10.1145/2567948.2576930

Inferring international and internal migration patterns from twitter data. / Zagheni, Emilio; Garimella, Venkata Rama Kiran; Weber, Ingmar; State, Bogdan.

WWW 2014 Companion - Proceedings of the 23rd International Conference on World Wide Web. Association for Computing Machinery, Inc, 2014. p. 439-444.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Zagheni, E, Garimella, VRK, Weber, I & State, B 2014, Inferring international and internal migration patterns from twitter data. in WWW 2014 Companion - Proceedings of the 23rd International Conference on World Wide Web. Association for Computing Machinery, Inc, pp. 439-444, 23rd International Conference on World Wide Web, WWW 2014, Seoul, Korea, Republic of, 7/4/14. https://doi.org/10.1145/2567948.2576930
Zagheni E, Garimella VRK, Weber I, State B. Inferring international and internal migration patterns from twitter data. In WWW 2014 Companion - Proceedings of the 23rd International Conference on World Wide Web. Association for Computing Machinery, Inc. 2014. p. 439-444 https://doi.org/10.1145/2567948.2576930
Zagheni, Emilio ; Garimella, Venkata Rama Kiran ; Weber, Ingmar ; State, Bogdan. / Inferring international and internal migration patterns from twitter data. WWW 2014 Companion - Proceedings of the 23rd International Conference on World Wide Web. Association for Computing Machinery, Inc, 2014. pp. 439-444
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