Sentiment analysis of social media and comment data is an important issue in opinion monitoring. In this work, we propose a Linguistic-Aware Attention Network (LANN) to enhance the performance of convolution neural network (CNN). LANN adopts a two-stage strategy to model the sentiment-specific sentence representation. First, an interactive attention mechanism is designed to model word-level semantics. Second, to capture phrase-level linguistic structure, a dynamic semantic attention is adopted to select the crucial phrase chunks in the sentence. The experiments demonstrate that LANN has robust superiority over competitors and has reached the state-of-the-art performance.
CITATION STYLE
Lei, Z., Yang, Y., & Liu, Y. (2018). LAAN: A Linguistic-Aware Attention Network for Sentiment Analysis. In The Web Conference 2018 - Companion of the World Wide Web Conference, WWW 2018 (pp. 47–48). Association for Computing Machinery, Inc. https://doi.org/10.1145/3184558.3186922
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