Ongoing Project:

Designing National Immigration Policies in a Rapidly Globalizing World: The Impact of Digital Interconnectedness on Policies and Views on Immigration in Canada

Researchers: Abdie Kazemipur1, Roozbeh Safshekan2
Affiliation: University of Calgary1, Massachusetts Institute of Technology (MIT)2
Keywords: refugees, immigrants, public opinion, policy, social attitudes, globalization, digital information, social media, absorptive capacity


Overview: This study uses artificial intelligence and automated content analysis to investigate parliamentary deliberations and social media content in Canada and compare emerging patterns to those in France and the U.S to understand how globalization affects policy and social attitudes.

Objective: to understand how the global spread of digital information affects policies and societal views on immigration and refugees in Canada.

Research Justification: The influx of large numbers of refugees in relatively short periods has often resulted in backlash by local populations and right-wing populism among politicians. Such backlash and resultant anti-immigrant and anti-refugee discourses can easily travel from one country to another due to the digitization of information and social media. The guiding hypothesis for this study is that the global interconnectedness of policy and social views makes immigration discourses globalized, overshadowing the particularities of the local immigration contexts. This, in turn, can create tension between the government and public about immigration issues. The research findings will offer predictions for the future trajectories of immigration and refugee discourses and policies in democratic countries like Canada.


The study uses the conceptual framework of ‘absorptive capacity’ – the capacity of the existing housing market, job market, and education system to accommodate an increase in the number of admitted immigrants. This concept is extended to ‘social absorptive capacity’ – the degree to which new immigrants are accepted and welcomed by the general population – and ‘political absorptive capacity’ – the dynamics of governmental thinking about immigration. 

The research team will examine recent technical capabilities introduced through artificial intelligence, machine learning, and big-data analytics applied to existing surveys of public opinions on immigration, the contents of social media, and the comments’ section of online newspaper and magazine articles. Using these tools, it will be possible to analyze large amounts of textual contents, audio files, and images in order to arrive at underlying patterns in the data.

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