  Positive thinking is thought to be an important component of self-motivation
in various practical fields such as education and the workplace. Previous work,
including sentiment transfer and positive reframing, has focused on the
positive side of language. However, self-motivation that drives people to reach
their goals has not yet been studied from a computational perspective.
Moreover, negative feedback has not yet been explored, even though positive and
negative feedback are both necessary to grow self-motivation. To facilitate
self-motivation, we propose CArrot and STICk (CASTIC) dataset, consisting of
12,590 sentences with 5 different strategies for enhancing self-motivation. Our
data and code are publicly available at here.
