It not only has a variety of practical applications, e.g., fighting offensive language on social media (dos Santos et al., 2018), but also serves as an ideal testbed for controllable text generation.
in addition, we train the sentiment classifier (Kim, 2014) to filter samples with the category confidence below 0.8.