Sentence Modeling with Deep Neural Architecture using Lexicon and Character Attention Mechanism for Sentiment Classification

Huy-Thanh Nguyen, Minh-Le Nguyen
2017 International Joint Conference on Natural Language Processing  
Tweet-level sentiment classification in Twitter social networking has many challenges: exploiting syntax, semantic, sentiment and context in tweets. To address these problems, we propose a novel approach to sentiment analysis that uses lexicon features for building lexicon embeddings (LexW2Vs) and generates character attention vectors (Char-AVs) by using a Deep Convolutional Neural Network (DeepCNN). Our approach integrates LexW2Vs and CharAVs with continuous word embeddings (Continu-ousW2Vs)
more » ... d dependency-based word embeddings (DependencyW2Vs) simultaneously in order to increase information for each word into a Bidirectional Contextual Gated Recurrent Neural Network (Bi-CGRNN). We evaluate our model on two Twitter sentiment classification datasets. Experimental results show that our model can improve the classification accuracy of sentence-level sentiment analysis in Twitter social networking.
dblp:conf/ijcnlp/NguyenN17 fatcat:65duaogigndj3ek4foalca6ojq