Amazon_Vine_Analysis

Overview of the analysis:

• The purpose of this project is to analyze Amazon reviews written by members of the paid Amazon Vine program, a service that allows manufacturers and publishers to receive reviews of their products and determine if there are any biases between Vine members and Non-Vine member's reviews.
• We use PySpark to perform the ETL process to extract the dataset, transform the data, connect to an AWS RDS instance, load the transformed data into pgAdmin and calculate different metrics.
• We focused on the US reviews for softwares.

Results:

Total number of reviews

• Vine reviews

• Non-Vine reviews

Total number of 5-star reviews

• Vine reviews

• Non-Vine reviews

Percentage of 5-star reviews

• Vine reviews

• Non-Vine reviews

Summary

• For the software category, 41% of the reviews in the Vine program were 5 stars reviews whereas the percentage in the non-Vine reviews is only 29%. This describes a positivity bias for reviews in the Vine program.
• We could perform additional analysis on the statistical distribution (mean, median and mode) of the star rating for the Vine and non-Vine reviews.