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The ability of party leaders to influence their party members to support the party line on public policy has long been an indicator of a strong, cohesive political party. In the United States party discipline has largely taken the form of patronage or earmarks, which provided local benefits in the form of localized spending to legislators in exchange for their deference to the party line. With the Congressional ban of earmarks in 2011, party leaders must resort to alternative forms of punishment and reward to encourage party members to behave in line with the party. In the absence of monetary incentives, party leaders have turned to alternative forms of punishment and reward for party members. Electoral endorsements and public messages to increase public support for party members is one way that party leaders can discipline their party. The digital media era provides party leaders with greater opportunities to direct messages of support or opposition to the general public. Social media specifically creates opportunities for party leaders to spread messages to constituents, specifically to the constituents of party members. This study examines the use of Twitter by Presidents Obama and Trump to discipline their party. Using Named Entity Recognition machine learning on a large (n=22980) corpus of Tweets, we are able to extract incidents where Presidents mention party members by name. We then conduct both network analysis and sentiment analysis to determine the tone and direction of presidential tweets. This research can help illuminate how Presidents are opting to utilize social media, while also exploring party dynamics in a digital age.