🎓 College Event Feedback Analysis – Internship Project
✨ Use data science to improve campus life! Learn how to turn student feedback into actionable insights using real-world tools like Google Colab, pandas, and TextBlob — no coding background needed.
🔍 Project Overview
College events like tech fests, workshops, and cultural activities collect feedback — but are we using it meaningfully?
In this project, interns will analyze text and rating-based feedback submitted by students after attending campus events. You’ll work with simulated or real Google Forms data (CSV) and use basic Natural Language Processing (NLP) to understand satisfaction levels and identify areas for improvement.
🎯 What You’ll Do
- ✅ Clean and prepare feedback data (from a Google Form export)
- ✅ Analyze ratings (1–5 scale) to find patterns of satisfaction
- ✅ Use NLP tools to score sentiment in comments (positive/neutral/negative)
- ✅ Visualize trends with beautiful charts and graphs
- ✅ Suggest improvements for future events
🧠 Skills You’ll Gain
- Data cleaning & preparation with pandas
- Sentiment analysis using
TextBloborVADER - Creating bar charts, pie charts, word clouds for reports
- Interpreting survey data to help make real decisions
- Working in Google Colab (no software installation!)
🛠 Tools & Libraries
| Tool | Purpose |
|---|---|
| Google Colab | Online coding (no setup needed) |
| pandas | Data manipulation |
| seaborn/matplotlib | Visualization |
| TextBlob / VADER | Sentiment analysis (NLP) |
🗂️ Sample Dataset (CSV format)
Use any of these or simulate your own:
- 🔗 Student Feedback Survey Responses
- 🔗 Student Satisfaction Survey
- 📄 Or collect data from a real Google Form:
- Ask students to rate and comment after an event.
- Export the responses as CSV.
- You’re ready to analyze!
📊 Example Insights You Can Find
- Top 3 events with highest satisfaction
- Most common complaints from comments (via word cloud)
- Correlation between ratings and event type (workshop vs seminar)
- Which departments hosted the most-liked events
🎥 YouTube Tutorials for Beginners (for Reference)
- 📌 Google Colab for Beginners – FreeCodeCamp
- 📌 Sentiment Analysis in Python – TextBlob
- 📌 Plotting Data in Python (Seaborn/Matplotlib)
📁 Final Deliverable
✅ A clean, well-commented Jupyter Notebook (or Colab link)
✅ A mini-report/dashboard with:
- Graphs of ratings
- Sentiment analysis summary
- Key recommendations for event organizers