Deep learning CNN-LSTM framework for Arabic sentiment analysis using textual information shared in social networks
Bibliographic Data
| ID | 4659552 |
|---|---|
| Authors | Abubakr H Ombabi (0000-0003-4120-6702, Sudan University of Science and Technology, corresponding author), Wael Ouarda (0000-0002-6338-7092, University of Sfax), Adel M Alimi (0000-0002-0642-3384, University of Sfax) |
| Year | 2020 |
| Volume | 10 |
| Issue | 1 |
| Publication date | 2020-12-01 |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | Social Network Analysis and Mining (JOURNAL) |
| Journal identifiers | ISSN: 1869-5450 • E-ISSN: 1869-5469 |
| Publisher | Springer Science and Business Media LLC (PUBLISHER) |
| DOI | 10.1007/s13278-020-00668-1 |
| OpenAlex | W3038402194 |
| Language | EN |
| Citations received | 5 |
| References cited | 53 |
Deep learning · Embedding · Feature engineering · Feature extraction · Linguistics · Machine learning · Natural language processing · Sentiment analysis · Support vector machine · Word embedding · Advanced Text Analysis Techniques · Computer Science · Sentiment Analysis and Opinion Mining · Topic Modeling · Artificial Intelligence
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| Citations per year | 0.83 |
|---|---|
| Citation span | 2020 - 2024 (5) |
| Highly cited | No |