# A novel ensemble approach for Twitter sentiment classification with ML and LSTM algorithms for real-time tweets analysis

**Type:** Papers  
**Canonical URL:** https://scholariq.org/papers/a-novel-ensemble-approach-for-twitter-sentiment-classification-with-ml-and-lstm/

## Facts

| Field | Value |
| --- | --- |
| Author Names | T. V. Krishna,Tummalapalli Siva Rama Krishna,Srinivas Kalime,Chinta Venkata Murali Krishna,S. Neelima,Raja Rao PBV |
| Citations | 13 |
| DOI | 10.11591/ijeecs.v34.i3.pp1904-1914 |
| Fields | Computer Science |
| Open Access | true |
| OA Status | diamond |
| OA URL | https://ijeecs.iaescore.com/index.php/IJEECS/article/download/36672/18344 |
| OpenAlex ID | https://openalex.org/W4394006081 |
| Type | article |
| Year | 2024 |

## Paper authors

- [S. Neelima](https://scholariq.org/researchers/s-neelima/)

## Paper journal

- [Indonesian Journal of Electrical Engineering and Computer Science](https://scholariq.org/journals/indonesian-journal-of-electrical-engineering-and-computer-science/)

## 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/)
- [Spam and Phishing Detection](https://scholariq.org/topics/spam-and-phishing-detection/)
- [Web Data Mining and Analysis](https://scholariq.org/topics/web-data-mining-and-analysis/)

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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.