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This paper uses unsupervised machine learning to uncover the topic structure of emails sent by presidents to their core supporters and generate measures of the mixtures of presidential presentation strategies used in their communications over time. Application of Topics over Time (TOT) topic modeling to emails sent throughout the Obama and Trump administrations allows for the comparison of both presidents' strategies for maintaining base support. The findings illustrate several strategies used by both presidents to maintain the trust of their core supporters in polarized times, as well as their relevance for the Biden presidency.