This assumption seems reasonable given that the voting population was strongly polarized during the general (post-primary) election season, and it doubles the amount of data we can use to train the models.
throughout this work the labels we use are taken from the set {"Support Trump / Oppose Clinton" = −1, "Neutral / I don't know" = 0, "Oppose Trump / Support Clinton" = 1}.