Using Twitter Data to Monitor Immigration Sentiment

Francisco Rowe [@fcorowe]¹, Michael Mahony¹, Eduardo Graells-Garrido [@carnby]², Marzia Rango [@MarziaRango]³, Niklas Sievers [@niklas_sievers ]³

¹ Geographic Data Science Lab, University of Liverpool, Liverpool, United Kingdom

² Barcelona Supercomputing Center, Barcelona, Spain

³ Global Migration Data Analysis Centre (GMDAC), International Organization for Migration, Berlin, Germany

Description

This repository contains the relevant data and code to replicate the analysis and results reported in the chapter "Using Twitter Data to Monitor Immigration Sentiment", Harnessing Data Innovation for Migration Policy: A Handbook for Practitioners published by International Organization for Migration.*.

Paper aim

To illustrate how immigration sentiment can be measured and monitored using Twitter data and natural language processing

Citation

If you use the code and/or data in this repository, we would appreciate if you could cite the pre-print paper as:

@incollection{rowe2023chp,
  title={Using Twitter Data to Monitor Immigration Sentiment},
  author={Rowe, Francisco and 
          Mahony, Michael and 
          Graells-Garrido, Eduardo and
          Rango, Marzia and
          Sievers, Niklas},
  booktitle={Harnessing Data Innovation for Migration Policy: A Handbook for Practitioners},
  pages={104-119},
  year={2023},
  url={https://publications.iom.int/books/harnessing-data-innovation-migration-policy-handbook-practitioners},
  publisher={International Organization for Migration. United Nations},
  city={Geneva}
}

Data