  From a crowded field with 17 candidates, Hillary Clinton and Donald Trump
have emerged as the two front-runners in the 2016 U.S. presidential campaign.
The two candidates each boast more than 5 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 three dimensions of social demographics: social capital,
gender, and age. 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
profile images to infer gender and age. For classifying gender, 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. Lastly,
middle-aged individuals are more likely to leave Trump, and the young are more
likely to leave Hillary Clinton.
