Emotional Analysis On Twitter Data

Overview:

The Emotional-Analysis-on-Twitter-data is a tool that scrapes tweets from Twitter and performs emotional analysis on them. It consists of multiple components, including a Flask application, a dashboard made with Plotly-Dash API, and Python files for handling Twitter operations and predicting emotions. The tool also includes a Python notebook file that demonstrates every operation in the code, including exploratory data analysis (EDA) on the dataset.

Features:

• Twitter Data Scraping: The tool is capable of scraping tweets from Twitter using the provided Python script.
• Emotional Analysis: It performs emotional analysis on the scraped tweets, predicting the emotional content of each tweet.
• Flask Application: The tool includes a Flask application that serves as the application framework for the webpage on Heroku.
• Plotly-Dash Dashboard: The dashboard is built using Plotly-Dash API, providing a visual representation of the emotional analysis results.
• Python Files: The tool consists of multiple Python files, including emotionalanalysis.py for predicting emotions and twitterscrape.py for handling Twitter-related operations.
• Python Notebook: The provided Python notebook file (Notebook.ipynb) demonstrates all the operations in the code and includes EDA on the dataset.

Summary:

Emotional-Analysis-on-Twitter-data is a tool that scrapes tweets from Twitter, performs emotional analysis on them, and provides a visual representation of the results through a Flask application and a Plotly-Dash dashboard. It includes Python files for predicting emotions, handling Twitter operations, and a notebook file for demonstrating all the operations in the code, including exploratory data analysis on the dataset. The installation process involves cloning the repository, installing the required dependencies for both the Flask application and the dashboard, and making any necessary modifications in the source code files.