[Objective] This paper proposes an end-to-end aspect-level sentiment analysis method based on BRNN, aiming to conduct fine-grained sentiment analysis for reviews of government APPs. [Methods] First, we built a neural network containing a two-layer BRNN structure and three functional modules. Then, we recognized the boundary and sentiment tendency of the government APP reviews, as well as extracted aspect entities. [Results] The proposed E2E-ALSA model had excellent classification and generalization ability. Its precision, recall and F1-score al...
