bfelbo/DeepMoji
State-of-the-art deep learning model for analyzing sentiment, emotion, sarcasm etc. observed · 2026-08-28
Health v2 · maintenance only
32/100
- Activity 0
- Release rhythm 35
- Longevity 100
Flags: no_releases
How is this computed?
round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10) — computed 2026-09-02. Adoption (stars, forks) is never an input.
- gap_med: n/a
- age_days: 3333
- days_rel: n/a
- days_push: 761
- n_releases_24m: 0
Adoption not part of the score
1554 stars · 307 forks observed · 2026-08-28
What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded
DeepMoji is a deep learning model trained on 1.2 billion tweets with emojis to understand emotional language, with code for scoring texts, encoding emotional feature vectors, and transfer learning. It is built on Keras with Theano or TensorFlow backends.
Use cases
- predict emojis for a piece of text
- analyze sentiment and emotion in tweets
- detect sarcasm in text
- extract emotional feature vectors from text
- fine-tune a pretrained model on a new emotion-related dataset
When to choose
- you need emotion or sarcasm analysis for short social media text
- you want a pretrained model for transfer learning on emotion-related NLP tasks
- you work in Python with Keras/TensorFlow
When to avoid
- you need a maintained Python 3 codebase out of the box
- you prefer PyTorch (use torchMoji instead)
- you need production-grade sentiment analysis for long-form or non-social-media text
Facets
library · maturity maintenance
machine-learning deep-learning nlp machine-learning deep-learning python sentiment-analysis emotion-detection transfer-learning emojis text-classification keras tensorflow natural-language-processing
1 source
- readme: https://github.com/bfelbo/DeepMoji · fetched 2026-08-28 · a619eec359da
Member repositories
| Repository | Role | Health v2 |
|---|---|---|
| bfelbo/DeepMoji | main | 32 |
For agents
Data as of 2026-08-30T08:39:29.467469+00:00 · Report a problem