https://github.com/sdpdas/sm_sentiment_analysis

Using Natural Language Processing (NLP) and pandas, numpy, scikit-learn for classification and applying logistic regression as it is a supervised model, lastly NLTK. Pickle library used for saving and running the model anywhere.
https://github.com/sdpdas/sm_sentiment_analysis

logistic-regression machine-learning nlp scikit-learn sentiment-analysis stemming vectorizer

Last synced: 26 days ago
JSON representation

Using Natural Language Processing (NLP) and pandas, numpy, scikit-learn for classification and applying logistic regression as it is a supervised model, lastly NLTK. Pickle library used for saving and running the model anywhere.

• Host: GitHub
• URL: https://github.com/sdpdas/sm_sentiment_analysis
• Owner: SDpDas
• License: mit
• Created: 2024-08-31T21:33:24.000Z (2 months ago)
• Default Branch: main
• Last Pushed: 2024-09-16T16:23:06.000Z (about 2 months ago)
• Last Synced: 2024-10-12T23:43:34.907Z (26 days ago)
• Topics: logistic-regression, machine-learning, nlp, scikit-learn, sentiment-analysis, stemming, vectorizer
• Language: Python
• Homepage:
• Size: 17.9 MB
• Stars: 0
• Watchers: 2
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

Awesome Lists containing this project

README

        
## Description

I have used sentiment analysis on 4 different datasets that focus on its tweets, ratings or reviews.

These are :

1. Twitter Dataset

2. Chat Dataset

3. Drugs review dataset

Three types of sentiment are covered - Positive, Negative and Neutral.

## Models Used

1. Logistic Regression

2. Multiclass LR

3. One vs Rest LR

4. Naive Bayes (Gaussian and Multinomial)

5. SVM with linear or rbf kernels

## Datasets used 

1. https://www.kaggle.com/datasets/abhi8923shriv/sentiment-analysis-dataset

2. https://www.kaggle.com/datasets/kazanova/sentiment140

3. https://www.kaggle.com/datasets/nursyahrina/chat-sentiment-dataset

4. https://www.kaggle.com/datasets/mohamedabdelwahabali/drugreview

## Colab Links  

1. Twitter model: https://colab.research.google.com/drive/1-IA0xgwLEJ1JcgpTRtjcTftv83ZggA-t?usp=sharing

2. Twitter model 2: https://colab.research.google.com/drive/1H--X9_GQy2D-59URXNHzCCQ7OJBsIqpX?usp=sharing

3. Chat model: https://colab.research.google.com/drive/1ndrjVt2CIc77pVsHQ1wa5hSrYTwkx8mC?usp=sharing

4. Drug review model: https://colab.research.google.com/drive/1hWVuJFKAOkGlYLWJR4KrdpVoS9Zkbr-i?usp=sharing

# Made by Sagardeep Das