IvayloP0709/Sentiment-Analysis-using-VADER-and-roBERTa
Comparative study of sentiment analysis techniques using VADER (rule-based) and roBERTa (transformer-based) models. Demonstrates the performance differences between traditional and deep learning approaches for text sentiment classification.
Stars
—
Forks
—
Language
Jupyter Notebook
License
—
Category
Last pushed
Feb 11, 2026
Commits (30d)
0
Get this data via API
curl "https://pt-edge.onrender.com/api/v1/quality/nlp/IvayloP0709/Sentiment-Analysis-using-VADER-and-roBERTa"
Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.
Higher-rated alternatives
3inchtime/douban_sentiment_analysis
基于朴素贝叶斯实现的豆瓣影评情感分析
MuhammedBuyukkinaci/TensorFlow-Sentiment-Analysis-on-Amazon-Reviews-Data
Implementing different RNN models (LSTM,GRU) & Convolution models (Conv1D, Conv2D) on a subset...
Robin-WZQ/Text-sentiment-polarity-judgment
基于规则、基于朴素贝叶斯、基于逻辑回归进行文本情感极性分析判断（酒店评论语料）
nhtlongcs/StarListify
StarListify is a Python package that classifies GitHub stars history into organized category...
sharmaroshan/Employee-Reviews
This is Project which contains Data Visualization, EDA, Machine Learning Modelling for Checking...