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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]

The Covid-19 pandemic has led to widespread worries that the health crisis is resulting in generalized hostility towards minorities and reduced support for a diverse society. Relying on a large survey of diversity attitudes in Germany fielded before and during the pandemic, we employ a quasi-experimental design to evaluate whether such a trend has occurred among the general public. Past work suggests two competing expectations – one anticipating a rise in hostility grounded in threat theories, and one anticipating stability grounded in public opinion research and theories of longer-term value change. Empirical results reveal generally high assent to socio-demographic diversity and minority accommodation, and remarkable stability during the pandemic period. Additionally, survey vignettes show strong and equally stable anti-discrimination norms that are inclusive of Asian-origin populations. Overall, results suggest that surges in racist incidents during the pandemic do not reflect analogous surges in hostility within the population at large. [ABSTRACT FROM AUTHOR]