The Swedish immigration discourse in traditional media and social media
Title: The Swedish immigration discourse in traditional media and social media
SNIC Project: SNIC 2021/5-537
Project Type: SNIC Medium Compute
Principal Investigator: Marc Keuschnigg <marc.keuschnigg@liu.se>
Affiliation: Linköpings universitet
Duration: 2021-12-01 – 2022-12-01
Classification: 50401 10208
Homepage: https://liu.se/en/research/computational-text-analysis
Keywords:

Abstract

Sweden has a rich and diverse immigration record starting after WWII and up until the present times. Naturally, societal perturbations caused by the inflows of immigrants motivate the growth of public debate on immigration. Recent developments of natural language processing in combination with large-scale archives of digitized texts enable the researchers to study discussion around the topic of immigration on an unprecedented scale with the finest level of granularity. In this project, we employ the opportunities provided by the NLP toolkit and big textual data to study how traditional and social media in Sweden have been producing immigration discourse during the past 15 years. Having at hand the data from the big four Swedish newspapers, as well as from the largest Swedish online forum Flashback, we are modelling the dependencies between the intensity of immigration debate in traditional and social media, and the dependencies between different understandings of immigration which appear in newspapers and on the online platform. We are aiming to understand the contribution of both kinds of media in shaping the immigration debate in Sweden, investigate the activity of different groups present on Flashback and how they react to the traditional media agenda. The combination of sociological knowledge and skills in statistics and text data analysis of the project team members puts us in the best position to study the multifaceted phenomena of immigration discourse based on the large corpora of texts. This project will be a continuation of the ongoing project SNIC 2020/05-604.