Name
Title | ||
|---|---|---|
Adaptive Recursive Neural Network For Target-Dependent Twitter Sentiment Classification |
Abstract | ||
|---|---|---|
We propose Adaptive Recursive Neural Network (AdaRNN) for target-dependent Twitter sentiment classification. AdaRNN adaptively propagates the sentiments of words to target depending on the context and syntactic relationships between them. It consists of more than one composition functions, and we model the adaptive sentiment propagations as distributions over these composition functions. The experimental studies illustrate that AdaRNN improves the baseline methods. Furthermore, we introduce a manually annotated dataset for target-dependent Twitter sentiment analysis. |
Year | Venue | Field |
|---|---|---|
2014 | PROCEEDINGS OF THE 52ND ANNUAL MEETING OF THE ASSOCIATION FOR COMPUTATIONAL LINGUISTICS, VOL 2 | Sentiment analysis,Computer science,Recurrent neural network,Artificial intelligence,Natural language processing,Syntax,Machine learning |
DocType | Volume | Citations |
Conference | P14-2 | 56 |
PageRank | References | Authors |
1.53 | 11 | 6 |