Numbers tell stories, and what better to capture narratives than text itself? This study goes beyond traditional polling, capturing the nuances of public sentiment on immigration. By analyzing how people discuss immigration – the language they use, the concerns they express, and the frames they employ – we gain a deeper understanding of the complexity of immigration attitudes, making every voice count.  This "text-as-data" approach allows for the identification of emerging trends and concerns long before they manifest in survey polls, enabling policymakers to proactively address evolving public sentiment and tailor policies accordingly. I believe that measuring and responding to these shifting dynamics in tandem with adapting policies and political messaging can strengthen public engagement and support in Canadian democracy.

When analyzing public opinion data, I find myself asking, “whose opinion counts?” The perspective of immigrants is understudied in public opinion literature on immigration, despite representing an increasingly salient electoral demographic. My research breaks down generalizations by comparing immigration attitudes within and across native-born and immigrant populations, and how factors such as partisanship, race, and social identity accounts for variance in such attitudes. My findings highlight the limitations of treating “immigrants" as a homogenous group and emphasize the need for more nuanced and targeted approaches to understanding and engaging with public opinion research. Understanding the complexity and diversity within this key demographic is crucial for delivering targeted political information and fostering more inclusive and informed public discourse on immigration.