From a crowded field with 17 candidates, Hillary Clinton and Donald Trump have emerged as the two presidential nominees in the 2016 U. S. presidential election. The two candidates each boast more than 7 million followers on Twitter, and at the same time both have witnessed hundreds of thousands of people leave their camps. In this paper we attempt to characterize individuals who have left Hillary Clinton and Donald Trump between September 2015 and March 2016. Our study focuses on four dimensions of social demographics: social capital, gender, age and race. Within each camp, we compare the characteristics of the current followers with former followers, i.e., individuals who have left since September 2015. We use the number of followers to measure social capital, and use profile images to infer gender, age and race. For classifying gender and race, we train a convolutional neural network (CNN). For age, we use the Face++ API. Our study shows that for both candidates followers with more social capital are more likely to leave (or switch camps). For both candidates females make up a larger presence among unfollowers than among current followers. Somewhat surprisingly, the effect is particularly pronounced for Clinton. Middle-aged individuals are more likely to leave Trump, and the young are more likely to leave Hillary Clinton. Lastly, for both candidates, African Americans make up a smaller presence among unfollowers than among followers, and the effect is particularly strong for Hillary Clinton.