Experimental results for cross-domain sentiment classification on a benchmark dataset show that the word representations learnt using the proposed method statistically significantly outper-form a state-of-the-art domain-insensitive word representation learning method (Pennington et al., 2014), and several competitive baselines.
our proposed cross-domain word representation learning method is not specific to a particular task such as sentiment classification, and in principle, can be in applied to a wide-range of domain adaptation tasks.