Publications

Large Language Models (LLMs) such as ChatGPT are transforming how scientists conduct and validate research, offering promise as tools to improve scientific reproducibility. However, computational reproducibility and error detection remain expensive and labor-intensive. We experimentally test how collaboration between researchers and LLM assistants influences the reproduction of quantitative social science findings across different levels of AI autonomy. We randomly assigned 288 researchers to 103 teams working under three conditions: human-only, AI-assisted (using ChatGPT as a collaborative tool), or AI-led (ChatGPT operating with minimal human oversight). Teams reproduced published results from leading social science journals, detected coding errors, and proposed robustness checks. Human-only and AI-assisted teams achieved comparable reproduction rates (94% vs. 91%) and performed similarly on most outcomes, except human-only teams identified significantly more major coding errors. Both substantially outperformed AI-led teams, which achieved only a 37% reproduction rate, detected fewer errors across all categories, proposed weaker robustness checks, and required more time. This autonomous approach, however, likely represents only a lower bound of AI capabilities. Despite rapid model advances, expert human judgment currently remains indispensable for reliable empirical verification. While AI assistance did not degrade most outcomes, it provided no measurable advantages and was associated with reduced detection of major errors. However, the 37% autonomous reproduction rate indicates that AI could provide value in settings where scale or cost constraints preclude human review of papers, even though general-purpose LLMs offer no immediate advantages for human-supervised verification.

Science aspires to be cumulative. Reproducibility efforts strengthen science by testing the reliability of published findings, promoting self-correction, and informing policy-making. Here we reproduced original analyses and conducted robustness checks of 110 articles published in leading economics and political science journals with mandatory data and code sharing policies. We found that more than 85% of published claims were computationally reproducible. In robustness checks, our reanalyses showed that 72% of statistically significant estimates remain significant and in the same direction, and the median reproduced effect size is nearly the same as the originally published effect size (99% of the published effect size). Additionally, 6 independent research teams examined 12 pre-specified hypotheses about determinants of robustness. Research teams with more experience found lower levels of robustness, and robustness did not correlate with author characteristics or data availability.

The same dataset can be analysed in different justifiable ways to answer the same research question, potentially challenging the robustness of empirical science. In this crowd initiative, we investigated the degree to which research findings in the social and behavioural sciences are contingent on analysts' choices. We examined a stratified random sample of 100 studies published between 2009 and 2018, in which, for one claim per study, at least five reanalysts independently reanalysed the original data. We found that 34% of the independent reanalyses yielded the same result as the original report; with a four times broader tolerance region, this increased to 57%. Of the reanalyses conducted, 74% reached the same conclusion as the original investigation, 24% yielded no effects or inconclusive results and 2% reported the opposite effect. This exploratory study indicates that the common single-path analyses in social and behavioural research should not be simply assumed to be robust to alternative analyses.

This paper examines the long-term impact of past political processes and events on current perceptions of immigration. As a case study, we focus on contemporary public perceptions of migrants by citizens of the Baltic states and ask how historical migration patterns and policies within the former Soviet Union are reflected in these perceptions. Our analysis is based on original survey data collected from nationally representative samples in Estonia, Latvia, and Lithuania. Employing structural topic modeling (STM), we analyze over 1,100 responses to an open-ended survey question asking respondents to describe the group that comes to mind when thinking about immigrants in their country. Using STM allows us to identify socially meaningful themes, as highlighted by the respondents, and without bias from any predefined categories. Our findings demonstrate that, while Russia’s invasion of Ukraine featured significantly in the responses, the Soviet political legacy and the related Soviet era migration continue to shape perceptions of migrants in the Baltic States thirty years after their independence. Thus, even in the context of the most salient migration-related events, such as war, past geo-political processes can play a significant role in the formation of current public perceptions of immigration.

Antisemitism is a long-standing, yet recently escalating threat to Jews and social cohesion in general. While there are intense public debates on Muslim antisemitism, there is very little systematic research based on large-scale, representative data. We fill this gap by analysing approximately 8,500 respondents included in the German Integrationsbarometer 2020 survey. Our results demonstrate that antisemitism is significantly higher among Muslims compared to Christian or religiously unaffiliated respondents, and among immigrants from Turkey and the Middle East & North Africa compared to other groups. About 35 per cent of Muslims strongly agreed with classical antisemitic statements. Deeper analyses reveal that antisemitism is particularly high among Muslims who are very religious or less educated. On the other hand, antisemitism is much lower among Muslims who are less religious or highly educated. We find only limited support for the impact of the time since migration on the antisemitism levels of Muslims. The findings are robust to various operationalizations of classical antisemitism and modelling choices. We discuss the theoretical as well as political implications of our findings.

This study investigates researcher variability in computational reproduction, an activity for which it is least expected. Eighty-five independent teams attempted numerical replication of results from an original study of policy preferences and immigration. Reproduction teams were randomly grouped into a ‘transparent group’ receiving original study and code or ‘opaque group’ receiving only a method and results description and no code. The transparent group mostly verified original results (95.7% same sign and p -value cutoff), while the opaque group had less success (89.3%). Second-decimal place exact numerical reproductions were less common (76.9 and 48.1%). Qualitative investigation of the workflows revealed many causes of error, including mistakes and procedural variations. When curating mistakes, we still find that only the transparent group was reliably successful. Our findings imply a need for transparency, but also more. Institutional checks and less subjective difficulty for researchers ‘doing reproduction’ would help, implying a need for better training. We also urge increased awareness of complexity in the research process and in ‘push button’ replications.

This study investigates the relationship between major Jihadist terror attacks and manifestations of ethno-religious hostility on social media. Analyzing approximately 4.5 million time-stamped Tweets from 1.2 million users across five European countries, the study focuses on content discussing migration and related topics in the weeks before and after ten significant terror attacks. The findings show a notable and robust increase in hostile Tweets after an attack. An interrupted time series analysis demonstrates a 10% point surge at the time of the attack, followed by a gradual decline. Accordingly, the impact of such attacks on online hostility diminishes approximately seven days after the event. Further analyses reveal that while attacks have the strongest effect on Tweets about Muslims and Islam, the attacks also increase hostility in Tweets about migration in general. We find that the overall attack effect is driven by both intra-user changes in Tweeting and changes in the composition of users posting after an attack. The findings underscore the importance of understanding the interplay between terrorist events and online discourse, shedding light on the dynamics of ethno-religious hostility in the digital realm.

While exclusionary national identities are widespread among Europeans, relatively few people vote for the far right in most countries. Thus, an exclusionary identity in many cases does not lead to voting for the most nativist types of parties. We explain this empirical puzzle by showing that these identities need to be activated to become behaviourally relevant. To this end, we analyse longitudinal comparative data of over 135,000 individuals across more than 26 years and 26 countries combining different survey programmes and manifesto data. We use latent class analysis to show that over half of respondents hold exclusionary conceptions of nationhood. Moreover, this type of national identity predicts voting far right. Using multi‐level modelling and within‐country estimators, we further demonstrate that this relationship is significantly stronger when a country's political elites across all parties become more exclusionary. Taking the activation hypothesis to the test in a European context, we conclude that the effect of national identity is conditional on its prior activation.

Right-wing media are pivotal for the success of the political right. We investigate the discursive trends in roughly 57,000 articles published in Germany’s biggest far-right weekly newspaper, Junge Freiheit (JF), between 1997 and 2019. During this period, JF expanded steadily in terms of both circulation and output. Quantitative content analyses reveal that, firstly, JF shows clear partisanship: although officially independent, JF has already covered the relatively new right-wing party Alternative für Deutschland more than all other parties combined. Secondly, JF tends to form its identity mostly through railing against the perceived dominance of liberalism in politics and society, although attention to these aspects has decreased in recent years. At the same time, whitewashing Germany’s past has been a rather stable theme. Lastly, the JF clearly casts immigrants, refugees, and Muslims as a threat to Germany. However, this aspect has mainly become prominent in recent years, and the refugee inflows of 2015/16 worked as a catalyst that boosted attention on related topics. We discuss implications for scholarship on right-wing media in general, and Germany in particular.

Results from previous research suggest that terrorist attacks lead to relatively short‐term increases in trust in institutions. The explanation for this increase is known as the ‘rally effect’, whereby individuals respond to crises and threats with more positive support for political leaders and institutions. Even though the number of related natural experiments with survey data is increasing, these studies merely represent case studies of single incidents with limited external validity. To advance quasi‐experimental research on the effects of terrorist attacks on institutional trust, we propose a new methodological approach by assessing all jihadist terrorist attacks resulting in at least one civilian death in a European country that take place during the fieldwork of the European Social Survey and combining the results of eight unique natural experiments in five different countries using meta‐analytic and meta‐regression techniques. The results of this ‘multi‐site natural experiment’ indicate that support for the rally‐hypothesis is mixed at best. While some attacks appear to significantly increase at least some measures of institutional trust (e.g., The Netherlands 2004, France 2015, Israel 2012), others seem to have no effect at all (e.g., Germany 2015, France 2018), or even substantially decrease trust in domestic political institutions (Russia 2012). Summary effects from multilevel meta‐analyses are non‐significant for any institutional trust outcome. These results are robust to a large number of robustness tests and alternative specifications. In comparison with previous research, it appears that a lot of the European evidence for the rally‐hypothesis was based on ‘outlier’ case studies like the Charlie Hebdo attack in France, 2015. Accordingly, our results cast doubt on the unrestricted generalisability of rally effects after terrorist attacks to different geographic, political, social or historical contexts.

Exclusionist positions on immigration have become a key component of right-wing ideology in most countries around the world. Combining group threat and news values theory, this study sheds light on the emergence of right-wing discourses on immigration based on one of Germany’s most influential right-wing print outlets. I employ supervised and unsupervised machine-learning methods on almost 54,000 articles published between 1998 and 2019 to test whether real-world conditions shape immigration news. Results show that reporting on immigration generally increased over time and peaked during the refugee inflow in 2015/16. Immigration numbers, foreigner crime rates, and Jihadist terror attacks predict the salience of the immigration issue in the overall news as well as discursive shifts within immigration news. During times of high immigration, articles were more likely to address topics related to deportation and closing borders or the criminalization of immigration. Terrorism was more present in immigration news after attacks, especially after attacks in Germany. Foreigner crime did not significantly increase reporting on crime in immigration news. In short, right-wing immigration discourses seem responsive to real-world developments and events that enable exclusionary rhetoric and a threatening portrayal of immigrants.

Immigration is a hotly-debated topic in many countries around the world. We examine how immigration-related political elite discourses affect natives' attitudes towards immigration and how these discourses contribute to polarisation along political and socio-economic dimensions. Drawing upon longitudinal crossnational data from the European Social Survey over 18 years and a genuine within-country estimator for both country-level main effects and cross-level interactions, our results show that, controlling for actual immigration, anti-immigrant attitudes increase when political elites express more exclusionary sentiments towards immigration and decrease when political elites express more inclusionary sentiments. Deeper analyses reveal exclusionary political elite discourses primarily resonate with voters on the right, whereas the effects of inclusionary discourses do not vary with political orientation. We do not find any attitude polarisation between lower-and highly-educated individuals. In sum, our results indicate that ideological and discursive aspects of intergroup conflict are more important than real-world conditions.

This study explores how researchers’ analytical choices affect the reliability of scientific findings. Most discussions of reliability problems in science focus on systematic biases. We broaden the lens to emphasize the idiosyncrasy of conscious and unconscious decisions that researchers make during data analysis. We coordinated 161 researchers in 73 research teams and observed their research decisions as they used the same data to independently test the same prominent social science hypothesis: that greater immigration reduces support for social policies among the public. In this typical case of social science research, research teams reported both widely diverging numerical findings and substantive conclusions despite identical start conditions. Researchers’ expertise, prior beliefs, and expectations barely predict the wide variation in research outcomes. More than 95% of the total variance in numerical results remains unexplained even after qualitative coding of all identifiable decisions in each team’s workflow. This reveals a universe of uncertainty that remains hidden when considering a single study in isolation. The idiosyncratic nature of how researchers’ results and conclusions varied is a previously underappreciated explanation for why many scientific hypotheses remain contested. These results call for greater epistemic humility and clarity in reporting scientific findings.

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.

The relation between religiosity and well-being is one of the most researched topics in the psychology of religion, yet the directionality and robustness of the effect remains debated. Here, we adopted a many-analysts approach to assess the robustness of this relation based on a new cross-cultural dataset (N=10,535 participants from 24 countries). We recruited 120 analysis teams to investigate (1) whether religious people self-report higher well-being, and (2) whether the relation between religiosity and self-reported well-being depends on perceived cultural norms of religion (i.e., whether it is considered normal and desirable to be religious in a given country). In a two-stage procedure, the teams first created an analysis plan and then executed their planned analysis on the data. For the first research question, all but 3 teams reported positive effect sizes with credible/confidence intervals excluding zero (median reported β=0.120). For the second research question, this was the case for 65% of the teams (median reported β=0.039). While most teams applied (multilevel) linear regression models, there was considerable variability in the choice of items used to construct the independent variables, the dependent variable, and the included covariates.

The relationship between police and ethnic minorities has been the subject of increasing interest in many Western societies in recent years. We examine first-generation immigrants’ trust in the police in Europe from a comparative and longitudinal perspective. Based on roughly 20,000 immigrants observed in 22 countries over 13 years in the European Social Survey, results show that initially high levels of trust in the police among immigrants tend to erode with the length of their stay in the host country. We show that two simultaneous processes drive this pattern: a fading reference effect (downward assimilation) and an increasing discrimination effect. Cross-national comparisons show that, on average, immigrants in countries with more police trust the police less. However, there is no effect of police size within countries, mostly because police numbers hardly change over time. We discuss implications for future research and policy development based on our findings.

During the early months of the COVID-19 pandemic in Germany, social restrictions and social distancing policies forced large parts of social life to take place within the household. However, comparatively little is known about how private living situations shaped individuals experiences of this crisis. To investigate this issue, we analyze how experiences and concerns vary across living arrangements along two dimensions that may be associated with social disadvantage: loneliness and care. In doing so, we employ quantitative text analysis on open-ended questions from survey data on a sample of 1,073 individuals living in Germany. We focus our analyses on four different household structures: living alone, shared living without children, living with a partner and children, and single parents. We find that single parents (who are primarily single mothers) are at high risk of experiencing care-related worries, particularly regarding their financial situation, while individuals living alone are most likely to report feelings of loneliness. Those individuals living in shared houses, with or without children, had the lowest risk of experiencing both loneliness and care-related worries. These findings illustrate that the living situation at home substantially impacts how individuals experienced and coped with the pandemic situation during the first wave of the pandemic.

News media have transformed over the last decades, there being increasing numbers of online news suppliers and an increase in online news consumption. We examine how reporting on immigration differs between popular German online and print media over three crucial years of the so-called immigration crisis from 2015 to 2017. This study extends knowledge on the framing of the crisis by examining a period covering the start, peak, and time after the intake of refugees. Moreover, we establish whether online and print reporting differs in terms of both frame occurrence and variability. The period of the crisis provided an ideal test to see whether the focus of media reporting differed between online and print sources. Employing a most- similar- cases design based on (autonomous) online and print versions of three major German news outlets, we extract the dominant frames in almost 18,500 articles using algorithm-based topic modelling. While results indicate that many frames are more visible in either online or print media, these differences often do not follow theoretical expectations. Furthermore, online media are dominated by particular frames and, hence, show less diversity than print media. However, important key events happening during our period of investigation do not affect overall diversity of frames.

With a growing Muslim population, many European countries need to integrate Muslims into their societies. One aspect that can hinder successful integration are substantial differences in human values. This is because such values are consequential for attitudes as well as behavior. We compare basic human values between Muslim immigrants and non-Muslim natives in four European countries with distinct immigration histories and integration politics: Belgium, France, Germany, and Sweden. For most insightful comparisons, we contrast values of Muslim immigrants with those of Christian natives as well as those of non-religious natives. We employ data of more than 50,000 individuals based on the first eight waves of the European Social Survey. Our findings reveal significant differences in value priorities between Muslims, Christians and non-religious individuals in all four countries. Amongst other things, Muslim immigrants score particularly high in conservation values (security and tradition / conformity). At the same time, they also score higher in self-transcendence values (benevolence as well as universalism). While many of these findings are in line with theory and previous research, the higher score in universalism is unexpected. A potential explanation is the combination of religious traditionalism and discrimination experiences. In other words, religious traditions are associated with more conservative views, but being subject to marginalization can still result in an appreciation of equal opportunities. We find only limited support for differences in hedonism. Religiosity correlates with values of tradition and conformity for Muslim immigrants as well as for Christian natives. Thus, accounting for religiosity renders differences in these values between Muslims and other groups statistically insignificant. While most of these findings hold in all countries, differences are most pronounced in Sweden and lower in the other three countries, which is also true after accounting for differences in socio-economic status and religiosity between the three groups. This suggests that a combination of a country’s history of diversity and national integration policies either encourages the convergence of values or leads to a solidification of value differences between ethnic and religious groups. We discuss these political and social implications of our findings.

COVID-19 is having a tremendous impact on gender relations, as care needs have been magnified due to schools and day-care closures. Using topic modeling on over 1,100 open reports from a survey fielded during the first four weeks of the lockdown in Germany, we shed light on how personal experiences of the lockdown differ between women and men. Our results show that, in general, people were most concerned about social contacts and childcare. However, we find clear differences among genders: women worried more about childcare while men were more concerned about paid work and the economy. We argue that the COVID-19 pandemic is affecting women more heavily than men not only at the physical level of work (e.g. women are reducing more paid work hours than men), but also through increasing the division regarding the cognitive level of work (e.g. women are more worried about childcare work while men are about paid work). These developments can potentially contribute to a future widening of the gender wage gap during the recovery process.

We analyze whether the Islamist terror attack on the Christmas market in Berlin in 2016 had an impact on public opinion toward immigration in general and, since the attacker has entered Germany to apply for asylum, toward refugees in particular. An analysis of this natural experiment reveals a negative shift regarding the latter, while no differences are observed for the former. To shed more light on the driver of attitude change, we combine these findings with a quantitative content analysis of online media reporting about refugees before and after the attack. Mass media have long been considered to have an impact on exclusionary attitudes toward ethnic minorities. However, empirical evidence on this relationship remains largely anecdotal. We draw upon unsupervised machine learning to quantify the developments in reporting in three popular German online news websites. Results reveal that the attack had significant impact on media reporting on these websites. However, the strong focus on the attack was only short lived, quickly decreasing already in the second week after the attack. Linking media data to the public opinion data reveals no clear connection between reporting and attitudes. In contrast to theoretical expectations, descriptive evidence even shows that both follow almost opposite trends, since people changed their attitudes only weeks after the attack. We discuss potential explanations of these, at first sight, counterintuitive findings.

In 2015, the number of people seeking asylum in Europe skyrocketed. However, asylum applications were mainly concentrated in a few destination countries such as Germany, Austria, or Sweden. After the so-called EU-Turkey deal, asylum rates quickly dropped in subsequent years. I examine how these developments affected public opinion from both a static and a dynamic comparative perspective. The rapid and largely unpredicted rise in refugee numbers and their prominence in public debates make demographic changes potent drivers of out-group hostility. The analysis of data from over 50,000 individuals in 22 countries contained in the seventh and eighth waves of the European Social Survey shows that attitudes toward refugees do not simply follow trends in asylum applications. Significantly lowering refugee numbers, hence, did not counter anti-refugee sentiments in the European public. Based on intra-country variation over time, the model rather predicts an increase in negative attitudes during times of considerable demographic shifts. Deeper analyses reveal that this effect is stronger for conservative Europeans as well as for those who distrust EU-politics. Moreover, while a general willingness to help is associated with more openness toward refugees, actually experiencing foreigner inflow diminishes this link, suggesting limitations of humanitarian concerns. Results are stable across various modelling and sample choices and not driven by individual countries. In sum, these findings demonstrate the importance of temporal dynamics for the formation of attitudes toward refugees in contemporary Europe and point to potentially polarizing effects of immigration along ideological lines.

Immigration is among the most vividly discussed topics in Europe’s national parliaments in recent years, often with a particular emphasis on the inflow of Muslims. This article examines the link between articulations of national political parties (political elite discourses) and natives’ attitudes toward immigrants in Europe. It provides a nuanced view of this relationship by (i) distinguishing more (inclusionary) from less (exclusionary) immigration-friendly political elites and (ii) isolating natives’ openness toward two specific groups: Muslim immigrants and ethnically similar immigrants. Combining the European Social Survey with party manifesto data and other sources, the analysis reveals that political elite discourses perform better in explaining natives’ attitudes compared to national demographic or economic aspects. Native Europeans’ attitudes toward Muslim immigrants are more hostile in countries where political elites are more exclusionary and more welcoming where political elites are more inclusionary. In contrast, Europeans’ views on ethnically similar immigrants seem largely unaffected by exclusionary political elites. These findings suggest that political elites can play an important role in fostering or impeding immigrant integration by shaping public opinion, particularly toward more marginalized immigrant groups.

Mass media has long been discussed as an essential determinant of the threat perceptions leading to anti-immigration attitudes. The field of empirical research on such media effects is still comparatively young, however, and lacks studies examining precise measures of the media environment an individual is likely to be actually exposed to. We employ a nuanced research design which analyses individual differences in the yearly levels of both media salience and attitudes in panel data of 25,000 persons, who were at least interviewed twice, and a time span over 15 years, from 2001 to 2015. We find a substantive and stable positive effect: comparing periods of vivid discussions with times where the issue was hardly discussed in the German media results in an increase in the predicted probability of being very concerned by about 13 percentage points. Deeper investigations reveal that the media effect is most potent for individuals living in areas with lower share of ethnic minorities and for those with lower education or conservative ideology, stressing the importance of individual receptiveness. In sum, our findings strengthen the line of reasoning stressing the importance of discursive influences on public opinion and cast doubt on the argument that threat perceptions stem primarily from the size of ethnic out-groups.

Wir diskutieren ein Vignettendesign, welches auf der Ziehung einer d-effizienten Einzelstichprobe aus dem gesamten Vignettenuniversum basiert. Hierfür gehen wir zunächst auf die zugrundeliegende Annahme vernachlässigbarer Interaktionen zwischen Vignettenmerkmalen ein. Eine anschließende Simulation veranschaulicht potenzielle Konsequenzen einer Verletzung dieser Annahme für unsere, in der KZfSS 2016, 2 publizierten Vignettenstudie.

Based on an innovative design, combining a multi-factorial survey experiment with a longitudinal perspective, we examine changes in the public acceptance of immigrants in Germany from the beginning of the so-called ‘migration crisis’ to after the sexual assaults of New Year’s Eve (NYE) 2015/2016. In contrast to previous studies investigating similar research questions, our approach allows to differentiate changes along various immigrant characteristics. Derived from discussions making up the German immigration discourse during this time, we expect reduced acceptance especially of those immigrants who were explicitly connected to the salient events, like Muslims and the offenders of NYE. Most strikingly, we find that refugees were generally highly accepted and even more so in the second wave, whereas the acceptance of immigrants from Arab or African countries further decreased. Moreover, female respondents’ initial preference for male immigrants disappeared. Contrary to our expectations, we find no changes in the acceptance of Muslims. We conclude that (i) public opinion research is well advised to match the particular political and social context under investigation to a fitting outcome variable to adequately capture the dynamics of anti-immigrant sentiment and that (ii) the vividly discussed upper limits for refugees seem to be contrary to public demands according to our data.

Germany is currently experiencing a huge inflow of migrants. In this vignette study, we analyze how much different kinds of migrants are accepted in Germany. We investigate three different rights for migrants: the right to stay in Germany, the right to work in Germany and the right to receive social benefits. Our results show that people who flee from political persecution are much more accepted compared to migrants who come because of economic reasons. This is particularly true for the right to receive social benefits. On the other hand, our results suggest that there is a strong preference for high-skilled and culturally non-distant migrants. Concerns regarding individual competition on the job market seem to play only a minor role.

Immigration has been a vividly discussed topic in Europe in recent years, leading to increased polarisation in many Western societies. Combining sociology and communication sciences, I argue that immigration-related discourses influence exclusionary attitudes and ethnic resentment beyond actual demographic circumstances, as such discourses are potent activators of feelings of threat, especially regarding specific kinds of ethnic out-groups. I examine effects of mass media, political parties and public speakers on general as well as group-specific attitudes, analysing longitudinal, cross-national, and experimental data sources. General media salience affects general concerns about immigration. Specific kinds of discourses also have group-specific effects, depending on the overall tone and particular content. Discourse effects are significantly stronger for individuals with conservative ideology, lower education, or few daily experiences with foreigners. In sum, social scientists are well advised to pay attention to the discursive and political climate characterising a particular research setting.

Immigration is a hotly-debated topic in many countries around the world. We examine how immigration-related political elite discourses affect natives' attitudes towards immigration and how these discourses contribute to polarisation along political and socio-economic dimensions. Drawing upon longitudinal cross-national data from the European Social Survey over 18 years and a genuine within-country estimator, our results show that, controlling for actual immigration, anti-immigrant attitudes increase when political elites express more exclusionary sentiments and decrease when elites express more inclusionary sentiments. Exclusionary political elite discourses primarily resonate with voters on the right, whereas inclusionary discourse effects do not vary with political orientation. Our results indicate that ideological and discursive aspects of intergroup conflict are more important than real-world conditions.

Political polarization shapes how minority issues are discussed in public and parliamentary discourse, with implications for representation and policy. We examine the representation of migration and sexual minorities in all parliamentary speeches across Germany and the United Kingdom from 1980 to 2021, asking how parties contributed to shifts in the overall salience of the two minority issues, how language use differs between party groups, and how this evolved over time. We employ natural language processing techniques on roughly 143,000 speech parts in total. The results show that speeches on both issues increased notably over time for all parties in both countries. Linguistic polarization concerning the terminology used by political parties has intensified over the years. In both countries, right-leaning parties emphasized economic and security aspects more when discussing migration, whereas left-leaning parties focused more on normative and rights-based issues. Regarding sexual minorities, the rhetoric of left parties more often included terms relating to equality or discrimination, while right parties more often referred to aspects of marriage and morals.

Diese Studie untersucht den Zusammenhang zwischen lokalen Migrationsbewegungen auf Gemeindeebene und individueller Wahrnehmung islamistischer Bedrohung sowie der nachgelagerten Wahlpräferenz für die AfD im Bundesland Sachsen. Anhand der Umfrage „Sicherheit und Kriminalität in Sachsen“ aus dem Jahr 2022 analysieren wir Daten von 1559 Personen aus 22 Gemeinden. Entgegen der Konflikttheorie zeigen unsere Ergebnisse, dass Personen in Gemeinden mit höherer Zuwanderung in den letzten zehn Jahren weniger Sorgen vor Islamismus äußerten. Zudem wählen Personen in diesen Regionen mit geringerer Wahrscheinlichkeit die AfD, was teilweise über geringere Bedrohungswahrnehmungen vermittelt wird. Diese Befunde stützen die Kontakttheorie, die einen Abbau von Vorurteilen durch interethnischen Kontakt annimmt.

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.

This chapter advances a theoretical framework to understand within- and between-country variation in the level of stigmatization experienced by immigrant groups and their descendants over time. Since processes of stigmatization and destigmatization may unfold over generations, it is imperative for research to adopt a longer time horizon to identify the factors that lead to the emergence, persistence, and/or dissipation of stigma. Based on the observation that the labeling of some groups as 'migrants' does not always follow from actual histories of immigration, this framework treats 'migrant' as a social category. To guide future empirical research, this chapter introduces two analytical models. The first identifies the factors and processes responsible for stigmatization or destigmatization over time. The second presents five ideal-typical pathways that immigrants and their descendants may experience in relation to stigma: non-emergence, increase, reinforcement, reduction, and status reversal.