At its core, the task involves taking customer review data for a certain product as input and outputting a summary which includes the number of positive and negative sentiment-bearing phrases for the features of the product (screen, size, camera, etc.).

This project is broken into 7 sections:

1. Analyse the task.
2. Preprocess the data.
3. Extract relevant information.
4. Opinion Words Extraction.
5. Apply a relevant sentiment analysis algorithm and experiment with a model extension.
6. Report evaluation results.
7. Print summaries.

Relevant evaluation metrics are also reported throughout the different steps of my implementation indicated by blue boxes along with a dedicated final section.