# Deep Sentiment Classification and Topic Discovery on Novel Coronavirus or COVID-19 Online Discussions: NLP Using LSTM Recurrent Neural Network Approach

**Type:** Papers  
**Canonical URL:** https://scholariq.org/papers/deep-sentiment-classification-and-topic-discovery-on-novel-coronavirus-or-covid/

## Facts

| Field | Value |
| --- | --- |
| Author Names | Hamed Jelodar,Yongli Wang,Rita Orji,Shucheng Huang |
| Citations | 380 |
| DOI | 10.1109/jbhi.2020.3001216 |
| Fields | Computer Science,Social Sciences |
| Open Access | false |
| OA Status | closed |
| OpenAlex ID | https://openalex.org/W3035119815 |
| PMID | 32750931 |
| Type | article |
| Year | 2020 |

## Paper authors

- [Rita Orji](https://scholariq.org/researchers/rita-orji/)

## Paper journal

- [IEEE Journal of Biomedical and Health Informatics](https://scholariq.org/journals/ieee-journal-of-biomedical-and-health-informatics/)

## Paper primary topic

- [Sentiment Analysis and Opinion Mining](https://scholariq.org/topics/sentiment-analysis-and-opinion-mining/)

## Paper topics

- [Sentiment Analysis and Opinion Mining](https://scholariq.org/topics/sentiment-analysis-and-opinion-mining/)
- [Misinformation and Its Impacts](https://scholariq.org/topics/misinformation-and-its-impacts/)
- [Topic Modeling](https://scholariq.org/topics/topic-modeling/)

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Source: ScholarIQ — public research metadata, principally OpenAlex. See https://scholariq.org/sources/ for provenance and https://scholariq.org/methodology/ for what these figures mean.