Semantic-Analysis-for-Tweets-Data-Natural-Language-Processing-NLP

URL: https://github.com/AravindhGoud/Semantic-Analysis-for-Tweets-Data-Natural-Language-Processing-NLP

Description

This dataset contains tweets classified into one of four categories: Regular, Sarcasm, Figurative, and Irony. The goal is to analyze the sentiment and emotions conveyed in these tweets, along with their impact and classification. The project involves data transformation and text processing using R or Python, as well as sentiment analysis and emotion mining with visualizations such as histograms, density plots, bar plots, and pie charts. Deployment of the analysis is done through Streamlit.

Dataset

• Classes:
  • Regular
  • Sarcasm
  • Figurative
  • Irony

Results

The repository suggests performing sentiment analysis and emotion mining on the tweets, with visualization methods like histograms, density plots, bar plots, and pie charts, but specific results are not provided in the repository.

Implementation & Code

The repository contains code for text processing, sentiment analysis, and deployment using Streamlit.