Green Pass Community Sentiment Analysis Twitter

Abstract

1. Introduction

One of the hottest topics in Italy in the last months of 2021 concerns the introduction of the Super Green Pass to access indoor clubs, events, gyms, etc. This security measure entered into force on 6 December 2021 and in fact no longer allows access to various services to those who have not completed the vaccination cycle. For these reasons it was decided, for the development of the project, to analyze the impressions of the Italian Twitter community regarding the Super Green Pass, with the aim of understanding who are the users who write and interact on the platform and if there are specific communities among the users who have commented on the introduction of this extension. We also want to analyze the possible influencing nodes of the network and verify the sentiment around them.

The project has set itself the goal of analyzing the thoughts and interaction of Italian users through the social posts expressed through the Twitter platform on the day of the entry into force of the new measures. In particular, we want to research the reference hubs present on the network, but also the sentiment and emotions of peoples with respect to the new limitations.

The data was collected by Twitter using their API and Tweepy python package. All tweets were written on December 6th in italian languages. If you need the data files used just write me, I have not been reported here on github to comply with the twitter API policies. In particular all the collected tweet and the sentiment extracted for each tweet is available if you need them.

2. Objective

The project has set itself the goal of analyzing the thoughts and interaction of Italian users through the social posts expressed through the Twitter platform on the day of the entry into force of the new measures. In particular, we want to research the reference hubs present on the network, but also the sentiment and emotions of peoples with respect to the new limitations.

This project demonstrates how Jupyter Notebook, Python can be applied to a real-world Digital Marketing & SEO problem.

4. Technology Stack

5. System Requirements

General requirements for this technology stack — check the README for exact versions.

• Python 3.8 or later with Jupyter Notebook / JupyterLab (or Google Colab)
• pip for dependencies
• Python 3.8 or later
• pip / virtualenv for dependencies
• VS Code, PyCharm or Jupyter Notebook
• Git (to clone the repository)

6. Installation & Setup

git clone https://github.com/rconfa/GreenPass-Community-Sentiment-Analysis-Twitter.git
cd GreenPass-Community-Sentiment-Analysis-Twitter

Full setup instructions are in the project README.

7. Future Enhancements

Suggested extensions you can add to make this your own project.

• Export reports to Google Sheets or PDF
• Schedule weekly automated reports
• Add competitor comparison

8. Viva / Review Questions

Common questions examiners ask for projects in this domain.

1. Which marketing or SEO problem does this tool solve?
2. Which data sources or APIs does it use (Search Console, Analytics, social platforms)?
3. Which metrics or KPIs does it report and how are they calculated?
4. How could the output help a business make decisions?
5. How would you schedule it to run automatically?

9. Source Code & License

This project is developed by rconfa and published on GitHub under the GNU General Public License v3.0. Please follow the license terms and credit the original author when you use or modify this code.