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

These are ecosystem siblings—both are independent educational implementations of the same sentiment analysis pipeline (Naive Bayes, SVM, LSTM) applied to Twitter data, rather than tools designed to work together or compete for the same use case.

Maintenance 0/25
Adoption 10/25
Maturity 16/25
Community 25/25
Maintenance 0/25
Adoption 6/25
Maturity 8/25
Community 15/25
Stars: 1,643
Forks: 608
Downloads:
Commits (30d): 0
Language: Python
License: MIT
Stars: 20
Forks: 5
Downloads:
Commits (30d): 0
Language: Jupyter Notebook
License:
Stale 6m No Package No Dependents
No License 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-

soham2707/Twitter-Sentiment-Analysis-

This is a project of twitter sentiment analysis using machine learning(Support Vector Machines,Naive Bayes), deep learning(LSTM), Transformer(BERT,ROBERTA).

This project helps you understand public opinion by analyzing Twitter posts. You provide raw tweets, and it tells you whether the sentiment expressed in each tweet is positive, negative, or neutral. This is useful for product managers, brand strategists, or anyone needing to gauge public reaction to a topic.

social-listening brand-reputation public-opinion product-launch market-research

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