Name
Title | ||
|---|---|---|
A multi-task neural network for multilingual sentiment classification and language detection on Twitter. |
Abstract | ||
|---|---|---|
In this paper, we propose a novel approach for classifying both the sentiment and the language of tweets. Our proposed architecture comprises a convolutional neural network (ConvNet) with two distinct outputs, each of which designed to minimize the classification error of either sentiment assignment or language identification. Results show that our method outperforms both single-task and multi-task state-of-the-art approaches for classifying multilingual tweets.
|
Year | DOI | Venue |
|---|---|---|
2018 | 10.1145/3167132.3167325 | SAC 2018: Symposium on Applied Computing
Pau
France
April, 2018 |
Keywords | Field | DocType |
multitask classification, sentiment analysis, language detection, convolutional neural networks | Convolutional neural network,Computer science,Sentiment analysis,Language identification,Artificial intelligence,Natural language processing,Artificial neural network | Conference |
ISBN | Citations | PageRank |
978-1-4503-5191-1 | 2 | 0.41 |
References | Authors | |
21 | 3 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Jonatas Wehrmann | 1 | 30 | 5.42 |
| Willian E. Becker | 2 | 2 | 0.41 |
| Rodrigo C. Barros | 3 | 448 | 32.54 |