Intimate partner violence is a public health problem with increasing prevalence and harmful influence to both individuals and society. Automated screening for intimate partner violence is still an unsolved problem in academic research and practical applications. Current detection methods use self-reporting scales and in-person interviews, which are laborious, expensive, and often lack precision and sensitivity, making it essential to develop new approaches. This paper proposes a scalable and

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... htweight ubiquitous screening technique, validated via ground truth data collected through self assessment survey, for detecting signs of intimate partner violence by analyzing individual-level Google search histories. Initial analysis shows that there are temporal, textual, contextual differences in search behavior between individuals who have/haven't experienced intimate partner violence. Using these differentiating signals, we were able to build a model that can detect violence in intimate relationships with an F1 score of 0.80. Though preliminary, we hope our findings pave the way for the AI community to address this important public health problem.