abhilashmnair/Sarcasm-Detection-with-BERT-and-GCN

A sarcasm detection model using Bidirectional Encoder Representations for Transformers (BERT) and Graph Convolutional Networks (GCN) has shown state-of-art results against conventional models and vanilla transformer-based approaches.

31
/ 100
Emerging

This project helps developers build advanced sarcasm detection models. It takes text data as input and determines whether the text is sarcastic, outputting a classification. This is ideal for natural language processing engineers or researchers who need to enhance text analysis capabilities in their applications.

No commits in the last 6 months.

Use this if you are an NLP developer or researcher looking to implement a state-of-the-art sarcasm detection solution in your text analysis projects.

Not ideal if you are a non-developer seeking a ready-to-use tool for immediate sarcasm detection without coding.

natural-language-processing text-analysis sentiment-analysis machine-learning-engineering computational-linguistics
Stale 6m No Package No Dependents
Maintenance 0 / 25
Adoption 6 / 25
Maturity 16 / 25
Community 9 / 25

How are scores calculated?

Stars

17

Forks

2

Language

Python

License

MIT

Last pushed

Aug 16, 2024

Commits (30d)

0

Get this data via API

curl "https://pt-edge.onrender.com/api/v1/quality/nlp/abhilashmnair/Sarcasm-Detection-with-BERT-and-GCN"

Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.