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Recent work finds that nonviolent resistance by ethnic minorities is perceived as more violent and requiring more policing than identical resistance by ethnic majorities, reducing its impact and effectiveness. We ask whether allies--advantaged group participants in disadvantaged group movements--can mitigate these barriers. On the one hand, allies can counter negative stereotypes and defuse threat perceptions among advantaged group members, while raising expectations of success and lowering expected risks among disadvantaged group members. On the other hand, allies can entail significant costs, carrying risks of cooptation, replication of power hierarchies, and marginalization of core constituencies. To shed light on this question we draw on the case of the Black Lives Matter (BLM) movement, which, in 2020, attracted unprecedented White participation. Employing a national survey experiment, we find that sizeable White presence at racial justice protests increases protest approval, reduces perceptions of violence, and raises the likelihood of participation among White audiences, while not causing significant backlash among Black audiences. Black respondents mostly see White presence as useful for advancing the movement's goals, and predominant White presence reduces expectations that protests will be forcefully repressed. We complement these results with analysis of tens of thousands of images shared on social media during the 2020 BLM protests, finding a significant association between the presence of Whites in the images and user engagement and amplification. The findings suggest that allyship can be a powerful tool for promoting sociopolitical change amid deep structural inequality. [ABSTRACT FROM AUTHOR]

Over the past decade, a large number of extremist and hate groups have turned to internet platforms to inspire mass violence. Currently, there is little reliable evidence on how such campaigns radicalize targeted audiences. We provide systematic, large-scale, microevidence on the effect of Islamic State propaganda on social media. We use several machine learning algorithms to detect recruitment messages in online propaganda, identify their dissemination on Twitter, and quantify the reactions of exposed users. Analyzing content produced by the Islamic State between 2015 and 2016 shows that propaganda conveying the material, spiritual, and social benefits of joining ISIS increased online support for the group, while content displaying brutal violence decreased endorsement of ISIS across a wide range of videos. Only the group's most extreme supporters reacted positively to violent propaganda. [ABSTRACT FROM AUTHOR]