SentiMap

Climate change is an urgent and critical global issue that threatens our planet and its inhabitants.

SentiMap is a data visualization software that allows users to gain crucial insights into public sentiments surrounding climate change.

It has two functionalities: display sentiment analysis and display carbon emissions analysis.

• Display sentiment analysis is accomplished by scraping Twitter tweets based on country inputted, using sentiment analysis to assign a sentiment (from very positive to very negative) to each tweet, and displaying it in a heatmap.
• Display carbon emissions analysis is accomplished by analysing a country's carbons emissions and displaying it in a heatmap.

Running the Program

Download the files and run the gui.py file.

Technical Documentation

The front-end is constructed with Python's TKinter module.

• gui.py contains the main window GUI.

The back-end is constructed using Folium and TextBlob.

• Carbon_map.py creates a carbon heatmap using Folium by reading a .csv file of the country entered.
• Sentiment_map.py creates a sentiment heatmap using Folium by scraping Twitter tweets based on the country entered and assigning sentiments to each tweet using TextBlob's natural language processing capabilities.

Note:

Sample carbon emissions and sentiment .csv files for USA and Canada are provided as testers since we did not have a Twitter API key to access tweets.