However, the performances of these works are highly dependent on manually annotated training data while annotation process is time-consuming and expensive.
cross-domain sentiment classification, which aims to transfer knowledge learned on labeled data from related domains * Equal contribution † Corresponding author (called source domain) to a new domain (called target domain), becomes a promising direction.