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While assimilation theories implicitly assume that immigrants' acceptance as "one of us" derives from their high levels of socioeconomic attainment in destination countries, little is known about the subjective experience of national belonging among the new immigrant elite in Western Europe. In this article, I assemble an analytical framework to study perceived acceptance within the national imagined community among immigrant-origin individuals who have already achieved high socioeconomic attainment at destination. Empirically, I look at subjective experiences of stigma and national belonging through in-depth interviews with forty-two professionals of North and Sub-Saharan African origins in France. How do these high-status individuals experience stigma, and how do they negotiate and claim inclusion as worthy members of the French imagined community? Respondents generally perceive only moderate levels of racial stigma in their daily lives, and I find that upper-middle-class culture empowers them to use cultural elitism to deflect racism as intellectually backward and illegitimate. However, I also find that self-identified Muslim respondents face widespread religious stigmatization that cast them as outsiders to French society. They respond to this stigmatization by distinguishing themselves from "undesirable" Muslims, rather than by denouncing anti-Muslim prejudice per se. These divergent experiences suggest that acceptance within the French nation is shaped by religious difference and remains actively negotiated after the achievement of social mobility. Overall, the paper suggests that cultural repertoires play a key role in enabling immigrant-origin individuals to claim national belonging in everyday life. [ABSTRACT FROM AUTHOR]

Computational social science provides an innovative set of methodological tools that can help answer questions of substantive interest to migration and integration research. In this introductory article, we first provide a brief history of how computational approaches have already enriched migration and integration research. Second, we identify several key promises of computational migration research (e.g. better access to hard-to-reach populations, cost reductions and time savings, better detection of causal mechanisms, avoidance of response biases and methodological nationalism through fine-grained, time-stamped, live digital trace data) and key challenges (e.g. missing categories, sampling issues, ethical concerns). Third, we illustrate how the contributions of this special issue fulfil some of these promises – as well as deal with the challenges – to gain new insights into key questions of migration and integration research that address why people emigrate, what the evolution of structural patterns in migration networks is, whether refugee movements can be predicted, how host communities respond to the influx of refugees, how people interpret, frame, and discuss these arrivals, how migration-related discourse responds to external shocks, and how spatial segregation patterns of migrants and ethnic minorities emerge. [ABSTRACT FROM AUTHOR]

In the last 20 years, several major terror attacks conducted in the name of political Islam hit Western Europe. We examine the impact of such terror attacks on hostile behaviour on social media from a cross-national perspective. To this end, we draw upon time-stamped, behavioural data from YouTube and focus on the frequency and popularity ('likes') of ethnically insulting comments among a corpus of approximately one hundred thousand comments. We study aggregate change and use individual-level panel data to investigate within-user change in ethnic insulting in periods leading up to and following major terror events in Germany, France and the UK. Results indicate that terror attacks boost interest in immigration-related topics in general, and lead to a disproportional increase in hate speech in particular. Moreover, we find that attack effects spill over to other countries in several, but not all, instances. Deeper analyses suggest, however, that this pattern is mainly driven by changes in the composition of users and not by changing behaviour of individual users. That is, a surge in ethnic insulting comes from hateful users newly entering online discussions, rather than previous users becoming more hateful following an attack. [ABSTRACT FROM AUTHOR]