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Based on a Digital Methods framework developed to map the policy influence of the CGIAR Research Program on Climate Change, Agriculture and Food Security (CCAFS) globally (Carneiro et al 2020), this study adapted the approach to focus on the Latin America regional program (LAM). The influence of CCAFS in LAM was explored through data analytics, with the application of machine learning techniques primarily focused on text mining, network analysis and hyperlink analysis of web-based sources. The foundation of this research is to assess the process of knowledge dissemination and influence of CCAFS activity to stakeholders and local beneficiaries, by considering online networks and narratives as evidence of “offline” program influence. It found that CCAFS plays a key role in raising awareness, building capacity, and supporting policy development around Climate-Smart Agriculture (CSA).