Adversarial interactions against politicians on social media such as Twitter have significant impact on society, and in particular both discourage people from seeking office and disrupt substantive political discussions online. There are many questions to be answered regarding this issue. Do politicians of certain gender or party affiliation receive more adversarial interactions? What are the unique challenges in automatically detecting adversarial interactions against political figures? Do users who engage in adversarial interactions exhibit different characteristics than those who don’t? In this talk, I will present our findings from a study conducted on a dataset of 400 thousand users' 1.2 million replies to the 756 candidates for the U.S. House of Representatives in the two months leading up to the 2018 midterm election on Twitter.