# Sentiment Analysis and Opinion Mining

**Type:** Topics  
**Canonical URL:** https://scholariq.org/topics/sentiment-analysis-and-opinion-mining-2/

## Facts

| Field | Value |
| --- | --- |
| Citations | 866,410 |
| Description | This cluster of papers focuses on sentiment analysis and opinion mining, particularly in the context of social media and text mining. It covers various techniques such as lexicon-based methods, deep learning, aspect-based sentiment analysis, and machine learning for analyzing emotions and opinions in textual data from platforms like Twitter. The research also delves into emotion recognition and the impact of sentiment analysis on public perception. |
| Domain | Physical Sciences |
| Field | Computer Science |
| OpenAlex ID | https://openalex.org/T10664 |
| Works | 69,033 |

## Topic researchers

Showing 12 of 20.

- [Yoshua Bengio](https://scholariq.org/researchers/yoshua-bengio/)
- [Kai Wang](https://scholariq.org/researchers/kai-wang-2/)
- [Christopher D. Manning](https://scholariq.org/researchers/christopher-d-manning/)
- [Francisco Herrera](https://scholariq.org/researchers/francisco-herrera/)
- [Richard Socher](https://scholariq.org/researchers/richard-socher/)
- [Philip S. Yu](https://scholariq.org/researchers/philip-s-yu/)
- [Andrew Y. Ng](https://scholariq.org/researchers/andrew-y-ng/)
- [Quoc V. Le](https://scholariq.org/researchers/quoc-v-le/)
- [Martin E. P. Seligman](https://scholariq.org/researchers/martin-e-p-seligman/)
- [Jure Leskovec](https://scholariq.org/researchers/jure-leskovec/)
- [Michael Berk](https://scholariq.org/researchers/michael-berk/)
- [Qiang Yang](https://scholariq.org/researchers/qiang-yang/)

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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.