When discussing politics, people often use subtle linguistic strategies to influence how their audience thinks about issues, which can then impact public opinion and policy. For example, anti-immigration activists may frame immigration as a threat to native born citizens’ jobs, describe immigrants with dehumanizing vermin-related metaphors, or even use coded expressions to covertly connect immigration with antisemitic conspiracy theories. In this talk, I will briefly overview my research program at the intersection of NLP, political framing, and implicitly harmful language, with a focus on computational approaches to analyze dogwhistle communication and metaphorical dehumanization. Grounded in an ongoing survey of computational research on antisemitism, I will also discuss the urgent need for group-specific resources, explainable models, and socially-grounded evaluation to understand implicit othering both in language analyzed with LLMs and in the models themselves.