# TWEERIFY: A Web-Based Sentiment Analysis System Using Rule and Deep Learning Techniques

**Type:** Papers  
**Canonical URL:** https://scholariq.org/papers/tweerify-a-web-based-sentiment-analysis-system-using-rule-and-deep-learning/

## Facts

| Field | Value |
| --- | --- |
| Author Names | Oluwatobi Noah Akande,Enemuo Stephen Nnaemeka,Oluwakemi Christiana Abikoye,Hakeem Babalola Akande,Abdullateef Oluwagbemiga Balogun,Joyce Ayoola |
| Citations | 4 |
| DOI | 10.1007/978-981-16-7182-1_7 |
| Fields | Computer Science |
| Open Access | false |
| OA Status | closed |
| OpenAlex ID | https://openalex.org/W4285232393 |
| Type | conference-paper |
| Year | 2022 |

## Paper authors

- [Joyce Ayoola](https://scholariq.org/researchers/joyce-ayoola/)

## Paper journal

- [Lecture notes on data engineering and communications technologies](https://scholariq.org/journals/lecture-notes-on-data-engineering-and-communications-technologies/)

## 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/)
- [Advanced Text Analysis Techniques](https://scholariq.org/topics/advanced-text-analysis-techniques/)

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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.