Trust plays an important role in helping online users collect reliable information, and has attracted increasing attention in recent years. We learn from social sciences that, as the conceptual counterpart of trust, distrust could be as important as trust. However, little work exists in studying distrust in social media. What is the relationship between trust and distrust? Can we directly apply methodologies from social sciences to study distrust in social media? In this paper, we design two computational tasks by leveraging data mining and machine learning techniques to enable the computational understanding of distrust with social media data. The first task is to predict distrust from only trust, and the second task is to predict trust with distrust. We conduct experiments in real-world social media data. The empirical results of the first task provide concrete evidence to answer the question, "is distrust the negation of trust?" while the results of the second task help us figure out how valuable the use of distrust in trust prediction.