Abstract:
Different product review analysis recently attracted the attention of natural language
processing specialists, thanks to positive customer comments and reviews spread around
the web. The increasing number of e-commerce sites leads to a rise in the purchasing rate
of various commodities. An illustration of this is the rapidly growing interest in literature
among the general public. In today's era of internet technology, Bangladesh's e-commerce
and online marketing sectors are already robust. Take online product reviews as an
example; they've really taken off as a go-to resource for shoppers. Some say that a book
is a person's closest companion. Books are indispensable for individuals as they offer
insights into the external world, enhance literacy skills, and bolster memory and intellect.
I aim to evaluate and rank reviews from Bangladesh and provide precise details on books
and online bookstores. I objective is to aid book enthusiasts in making informed decisions
when purchasing books and finding reliable online merchants. The word2vec and
FastText algorithms were utilized to transform text into numerical values. I used five
different classification algorithms, which are as follows: MNB, KNN, RF, SVC, and
XGboost Classifier or Multinomial Naïve Bayes. An accuracy of 85.92% was attained by
the Support Vector Classifier (SVC) using the FastText method.
