Data-Driven Perspectives on Outgroup Sentiment: Unmasking the Global Landscape with Social Data Science

Abstract

This study seeks to understand the influence of state level factors on an individual’s sentiment towards outgroups, identity groups to which a person does not belong. To identify these dynamics, I draw on national level data on ethnic group size and location, then link that to public opinion data from the World Values Survey. From this data, I create new measures from existing variables and harness multilevel modelling to better examine how the relative size of ethnic identity groups and their geographic location in a country influences intergroup attitudes and the acceptance of ethnic differences. I hypothesize that countries where ethnic groups live in distinctly separate areas from one another will experience more negative effect, particularly when the size of ethnic groups are sufficient to compete for political power. My project will create a new data set which will include a measure for outgroup sentiment, utilizing questions from the World Values Survey. From this dataset, I have also created a measure for group size by calculating individuals’ self-reported ethnic identity and inferring the approximate size of these groups within their given country. As a rise in outgroup hatred is seen across the globe, studies such as these are crucial. Trends towards a rise in populism throughout various countries underscore the urgency of understanding how national factors impact outgroup sentiment. This research, which examines the size and location of different ethnic groups and how that affects an individual’s opinion towards outgroups, not only advances scholarly knowledge but carries significant political and policy implications.