Name
Abstract | ||
|---|---|---|
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.
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Year | DOI | Venue |
|---|---|---|
2018 | 10.1145/3184558.3186922 | WWW '18: The Web Conference 2018
Lyon
France
April, 2018 |
DocType | ISBN | Citations |
Conference | 978-1-4503-5640-4 | 2 |
PageRank | References | Authors |
0.39 | 2 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Zeyang Lei | 1 | 23 | 4.01 |
| Yang Yu-Jiu | 2 | 89 | 19.30 |
| Yi Liu | 3 | 4 | 1.09 |