jazzykochar / amazon-fine-food-reviews

Semantic data analysis on amazon fine food review dataset to determine whether a review is positive or negative using various machine learning techniques.

Amazon-fine-food-reviews

Data Source: https://www.kaggle.com/snap/amazon-fine-food-reviews

Objective:

Given a review, determine whether the review is positive (Rating of 4 or 5) or negative (rating of 1 or 2).

Learning Outcomes

1. Text pre-processing using Natural Language Processing.

2. Data visualisation using t-sne algorithm.

Dataset Information

The Amazon Fine Food Reviews dataset consists of reviews of fine foods from Amazon.

Number of reviews: 568,454

Number of users: 256,059

Number of products: 74,258

Timespan: Oct 1999 - Oct 2012

Number of Attributes/Columns in data: 10

Attribute Information:

Id

ProductId - unique identifier for the product

UserId - unqiue identifier for the user

ProfileName

HelpfulnessNumerator - number of users who found the review helpful

HelpfulnessDenominator - number of users who indicated whether they found the review helpful or not

Score - rating between 1 and 5

Time - timestamp for the review

Summary - brief summary of the review

Text - text of the review