Sentiment and Emotion Analysis Visualization

This project involves crawling English, Malay and Chinese tweets related to the topic of “Online Learning” from Twitter, cleaning the crawled data, performing sentiment and emotion analysis and lastly, visualizing the result.

Table of Contents

1. About The Project
Built with
Sample Visualizations
2. Installation
3. Running the Project

About The Project

Due to the COVID-19 pandemic, many countries including Malaysia are under lockdown to contain the spread of the virus. As a result, teaching and learning activities are shifted online. As students, we are interested to find out what people think and feel about online learning. Therefore, this project is carried out to analyse the sentiments and emotions towards online learning on Twitter. This project was done in a group of 4 and I was responsible for visualizing the result of the sentiment and emotion analysis.

Built with

• HappyBase
• Flask
• Bootstrap
• Bokeh
• Matplotlib
• Wordcloud

Sample Visualizations

Language Proportion Pie Chart

Sentiment Proportion Pie Chart

Frequency over Time Line Graph

English Word Cloud

Sentiment by Day Stacked Bar Chart

Sentiment over Time Line Graph

Emotion Frequency Bar Chart

Emotion over Time Line Bar Chart

Installation

1. Download the Visualization folder.
2. Create a virtual environment and run the following command:
   

   pip install -r requirements.txt

Running the Project

1. Open app.py, go to the last line of the file, replace the host ip address with your own ip address.
2. Activate your virtual environment and change the directory to the project folder.
3. Run the following commands:

   set FLASK_APP=app.py
   set FLASK_ENV=development
   flask run

4. Access the webpage at localhost:5000 in your browser.