Sentiment Analysis Based on Deep Learning: A Comparative Study
Ho Chi Minh City University of Transport · Universidad de Salamanca
Abstract
The study of public opinion can provide us with valuable information. The analysis of sentiment on social networks, such as Twitter or Facebook, has become a powerful means of learning about the users’ opinions and has a wide range of applications. However, the efficiency and accuracy of sentiment analysis is being hindered by the challenges encountered in natural language processing (NLP). In recent years, it has been demonstrated that deep learning models are a promising solution to the challenges of NLP. This paper reviews the latest studies that have employed deep learning to solve sentiment analysis problems, such as sentiment polarity. Models using term frequency-inverse document frequency (TF-IDF) and…
Citation impact
- FWCI
- 40.37
- Percentile
- 100%
- References
- 67
Authors
3- NCNhan Cach DangCorresponding
Ho Chi Minh City University of Transport
- MNMaría N. Moreno-García
Universidad de Salamanca
- FDFernando De la Prieta
Universidad de Salamanca
Topics & keywords
- Sentiment analysis
- Word embedding
- Deep learning
- Word (group theory)
- Range (aeronautics)
- Embedding
- Term (time)
- Public opinion