The project aims to provide insights about Supercell's apps. I aim to find how positive or negative the review is so that this will lead to creating tailored response to the apps user and improve their experience.
Scraped Supercell's apps data from Google Play store and then stored the data into MongoDB. Creating visualization for the monthly score, review types (positive, negative), Identifying the comments compound score and finally creating a classification model to find how positive the review is.
Python Jupyter notebook IBM Watson Cload Canva Hitfilm Express MongoDB
Creating a video presentation to share with the staff of the company the visualization and insights for this project. Then suggest to them to deploy the model which will make it easy to respond to the app users by automating the response
Identifying the most popular reviews that got the most thumbs up and respond to them because it got attention for a reason. The most frequent words for the monthly reviews. Identifying if the app version is the reason for a certain review. Plotting the data into a BI tool for more visualisation