twitter-sentiment-analysis and Twitter-Sentiment-Analysis-

Maintenance 0/25
Adoption 10/25
Maturity 16/25
Community 25/25
Maintenance 2/25
Adoption 3/25
Maturity 15/25
Community 0/25
Stars: 1,643
Forks: 608
Downloads:
Commits (30d): 0
Language: Python
License: MIT
Stars: 3
Forks:
Downloads:
Commits (30d): 0
Language: Jupyter Notebook
License: MIT
Stale 6m No Package No Dependents
Stale 6m No Package No Dependents

About twitter-sentiment-analysis

abdulfatir/twitter-sentiment-analysis

Sentiment analysis on tweets using Naive Bayes, SVM, CNN, LSTM, etc.

This project helps social media analysts, marketers, or researchers understand public opinion by analyzing Twitter data. You provide a CSV file of tweets, some labeled as positive or negative, and it outputs predictions of sentiment for new, unlabeled tweets. It helps you quickly gauge sentiment trends without manual review.

social-media-analysis public-opinion brand-monitoring market-research text-analysis

About Twitter-Sentiment-Analysis-

muqadasejaz/Twitter-Sentiment-Analysis-

A machine learning project that analyzes the sentiment of tweets using a Support Vector Machine (SVM) classifier. The model is trained to classify tweets as positive, negative, or neutral based on the textual content, using NLP techniques like tokenization, TF-IDF vectorization, and data cleaning.

Scores updated daily from GitHub, PyPI, and npm data. How scores work