Mining for Meaning: The Dynamics of Public Discourse on Migration
Title: Mining for Meaning: The Dynamics of Public Discourse on Migration
SNIC Project: SNIC 2020/5-145
Project Type: SNIC Medium Compute
Principal Investigator: Marc Keuschnigg <marc.keuschnigg@liu.se>
Affiliation: Linköpings universitet
Duration: 2020-04-01 – 2021-04-01
Classification: 50401 10208
Homepage: https://liu.se/en/research/computational-text-analysis
Keywords:

Abstract

This VR-funded research environment seeks to understand how Sweden is adapting to modern migration and the integration of the newly-arrived. Bringing together relevant scholars with diverse methodological and substantive expertise, we combine cutting-edge research on migration and integration with the development of machine-learning applications for the analysis of text in the social sciences. Utilizing newly-available corpora of text as social sensors––collected from social-media sites, media repositories, and archives of parliamentary speeches and party manifestos––we analyze the dynamics of public discourse related to migration and integration. We apply novel tools of computational text analysis to measure meaning structures in the data and explain the processes by which collectively agreed-upon narratives arise from interactions between the public, the media, and political actors. We will gain understanding of the processes by which issues surrounding migration and integration are framed by different social groups, media outlets, and political parties, which will allow us to provide evidence-based policy recommendations that tackle key challenges of integration. Furthermore, our six-year research plan is integral to understanding evolving notions of inclusiveness in Swedish society because it will provide a glimpse into the emergence and transformation of the public debate on immigration.