Using twitter data to estimate the relationships between short-term mobility and long-term migration

Lee Fiorio, Emilio Zagheni, Guy Abel, Ingmar Weber, Jixuan Cai, Guillermo Vinué

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

8 Citations (Scopus)

Abstract

Migration estimates are sensitive to definitions of time interval and duration. For example, when does a tourist become a migrant? As a result, harmonizing across different kinds of estimates or data sources can be difficult. Moreover in countries like the United States, that do not have a national registry system, estimates of internal migration typically rely on survey data that can require over a year from data collection to publication. In addition, each survey can ask only a limited set questions about migration (e.g., where did you live a year ago? where did you live five years ago?). We leverage a sample of geo-referenced Twitter tweets for about 62,000 users, spanning the period between 2010 and 2016, to estimate a series of US internal migration flows under varying time intervals and durations. Our findings, expressed in terms of 'migration curves', document, for the first time, the relationships between short-term mobility and long-term migration. The results open new avenues for demographic research. More specifically, future directions include the use of migration curves to produce probabilistic estimates of long-term migration from short-term (and vice versa) and to nowcast mobility rates at different levels of spatial and temporal granularity using a combination of previously published American Community Survey data and up-to-date data from a panel of Twitter users.

Original languageEnglish
Title of host publicationWebSci 2017 - Proceedings of the 2017 ACM Web Science Conference
PublisherAssociation for Computing Machinery, Inc
Pages103-110
Number of pages8
ISBN (Electronic)9781450348966
DOIs
Publication statusPublished - 25 Jun 2017
Event9th ACM Web Science Conference, WebSci 2017 - Troy, United States
Duration: 25 Jun 201728 Jun 2017

Other

Other9th ACM Web Science Conference, WebSci 2017
CountryUnited States
CityTroy
Period25/6/1728/6/17

Keywords

  • Demographic research
  • Migration
  • Mobility
  • Twitter

ASJC Scopus subject areas

  • Computer Networks and Communications

Cite this

Fiorio, L., Zagheni, E., Abel, G., Weber, I., Cai, J., & Vinué, G. (2017). Using twitter data to estimate the relationships between short-term mobility and long-term migration. In WebSci 2017 - Proceedings of the 2017 ACM Web Science Conference (pp. 103-110). Association for Computing Machinery, Inc. https://doi.org/10.1145/3091478.3091496