This project analyzes responses collected from participants through a feedback form. The analysis is conducted using various approaches such as sentiment analysis, aspect-based sentiment analysis (ABSA), thematic analysis, and data visualizations. The primary goal is to derive actionable insights for enhancing future endeavors and providing better support.
- thematic.ipynb: Conducts thematic analysis to identify key themes in the feedback data.
- sentiment.ipynb: Performs sentiment analysis to classify feedback into positive, negative, and neutral categories.
- absa.ipynb: Executes aspect-based sentiment analysis to understand specific aspects of the feedback.
- visualizations.ipynb: Creates visualizations that include a bar chart and word clouds based on the analysis results.
- Ensure all required Python libraries are installed as mentioned in the notebooks.
- Open the notebooks in Google Colab or a similar environment to run the analyses and visualize the results.
- Data sources used include responses from Google Sheets and CSV files. Note that dummy links are used in the notebooks; replace them with links to your own data files for accurate processing.