/Twitter-Sentiment-Analysis-using-CNN

This project aims to perform sentiment analysis on a Twitter dataset using Convolutional Neural Networks (CNNs). The goal is to classify tweets into positive, negative, or neutral sentiments.

Primary LanguageJupyter Notebook

Twitter-Sentiment-Analysis-using-CNN

This project aims to perform sentiment analysis on a Twitter dataset using Convolutional Neural Networks (CNNs). The goal is to classify tweets into positive, negative, or neutral sentiments.

Key Features:

  • Utilizes a text dataset for sentiment analysis.
  • Implements various CNN architectures with different filter numbers and sizes.
  • Reports the results in a detailed PDF document.

Dataset:

The dataset used for this project is the Twitter Sentiment Analysis Dataset, which contains labeled tweets for sentiment analysis(https://www.kaggle.com/datasets/jp797498e/twitter-entity-sentiment-analysis).

CNN Architectures:

Different CNN architectures have been experimented with varying filter numbers and sizes to find the best model for sentiment analysis.

Results:

The results of the sentiment analysis experiments are summarized and presented in a PDF report.