Inspiration
Not many women clothing sites with proper review system. Not to mention women clothing can a fuss some time when it comes to fitting.
What it does
This is a Women’s Clothing E-Commerce dataset revolving around the reviews written by customers. Its nine supportive features offer a great environment to parse out the text through its multiple dimensions. Because this is real commercial data, it has been anonymized, and references to the company in the review text and body have been replaced with “retailer”.After analysis it tells whether the review is positive or negative or neutral.
How we built it
This dataset includes 23486 rows and 10 feature variables. Each row corresponds to a customer review, and includes the variables. In this dataset data cleaning is performed by dropping NaN vals. Changing the ratings to bad and good. Data Analysis and text preprocessing.
What we learned
As expected, review score is positively correlated to positive sentiment. Note that even among very low reviews, the sentiment is still positive which means that our negative words list is probably defficient. It could also mean that those who love a product can be more verbose if asked to describe their experience.
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